初始化项目，由ModelHub XC社区提供模型
Model: richardyoung/Qwen2.5-3B-Instruct-heretic Source: Original Platform
This commit is contained in:
ModelHub XC
36
.gitattributes
vendored
Normal file
36
.gitattributes
vendored
Normal file
@@ -0,0 +1,36 @@
|
|||||||
|
*.7z filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.arrow filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.bin filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ftz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.gz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.h5 filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.joblib filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.model filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.npy filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.npz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.onnx filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ot filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.parquet filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pb filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pickle filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pkl filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pt filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pth filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.rar filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
||||||
|
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tar filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tflite filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tgz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.wasm filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.xz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.zip filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.zst filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
||||||
146
README.md
Normal file
146
README.md
Normal file
@@ -0,0 +1,146 @@
|
|||||||
|
---
|
||||||
|
license: other
|
||||||
|
license_name: qwen-research
|
||||||
|
license_link: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE
|
||||||
|
language:
|
||||||
|
- en
|
||||||
|
pipeline_tag: text-generation
|
||||||
|
base_model: Qwen/Qwen2.5-3B
|
||||||
|
tags:
|
||||||
|
- chat
|
||||||
|
- heretic
|
||||||
|
- uncensored
|
||||||
|
- decensored
|
||||||
|
- abliterated
|
||||||
|
- reproducible
|
||||||
|
library_name: transformers
|
||||||
|
---
|
||||||
|
# This is a decensored version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct), made using [Heretic](https://heretic-project.org) v1.4.0
|
||||||
|
|
||||||
|
> [!TIP]
|
||||||
|
> **This model is reproducible!**
|
||||||
|
>
|
||||||
|
> See the [README](reproduce/README.md) in the `reproduce` directory for more information.
|
||||||
|
|
||||||
|
## Abliteration parameters
|
||||||
|
|
||||||
|
| Parameter | Value |
|
||||||
|
| :-------- | :---: |
|
||||||
|
| **direction_index** | 24.84 |
|
||||||
|
| **attn.o_proj.max_weight** | 1.47 |
|
||||||
|
| **attn.o_proj.max_weight_position** | 32.52 |
|
||||||
|
| **attn.o_proj.min_weight** | 1.29 |
|
||||||
|
| **attn.o_proj.min_weight_distance** | 19.99 |
|
||||||
|
| **mlp.down_proj.max_weight** | 1.05 |
|
||||||
|
| **mlp.down_proj.max_weight_position** | 21.22 |
|
||||||
|
| **mlp.down_proj.min_weight** | 0.98 |
|
||||||
|
| **mlp.down_proj.min_weight_distance** | 13.04 |
|
||||||
|
|
||||||
|
## Performance
|
||||||
|
|
||||||
|
| Metric | This model | Original model ([Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct)) |
|
||||||
|
| :----- | :--------: | :---------------------------: |
|
||||||
|
| **KL divergence** | 0.0494 | 0 *(by definition)* |
|
||||||
|
| **Refusals** | 3/100 | 96/100 |
|
||||||
|
|
||||||
|
-----
|
||||||
|
|
||||||
|
|
||||||
|
# Qwen2.5-3B-Instruct
|
||||||
|
|
||||||
|
## Introduction
|
||||||
|
|
||||||
|
Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:
|
||||||
|
|
||||||
|
- Significantly **more knowledge** and has greatly improved capabilities in **coding** and **mathematics**, thanks to our specialized expert models in these domains.
|
||||||
|
- Significant improvements in **instruction following**, **generating long texts** (over 8K tokens), **understanding structured data** (e.g, tables), and **generating structured outputs** especially JSON. **More resilient to the diversity of system prompts**, enhancing role-play implementation and condition-setting for chatbots.
|
||||||
|
- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.
|
||||||
|
- **Multilingual support** for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.
|
||||||
|
|
||||||
|
**This repo contains the instruction-tuned 3B Qwen2.5 model**, which has the following features:
|
||||||
|
- Type: Causal Language Models
|
||||||
|
- Training Stage: Pretraining & Post-training
|
||||||
|
- Architecture: transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings
|
||||||
|
- Number of Parameters: 3.09B
|
||||||
|
- Number of Paramaters (Non-Embedding): 2.77B
|
||||||
|
- Number of Layers: 36
|
||||||
|
- Number of Attention Heads (GQA): 16 for Q and 2 for KV
|
||||||
|
- Context Length: Full 32,768 tokens and generation 8192 tokens
|
||||||
|
|
||||||
|
For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwen2.5/), [GitHub](https://github.com/QwenLM/Qwen2.5), and [Documentation](https://qwen.readthedocs.io/en/latest/).
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
The code of Qwen2.5 has been in the latest Hugging face `transformers` and we advise you to use the latest version of `transformers`.
|
||||||
|
|
||||||
|
With `transformers<4.37.0`, you will encounter the following error:
|
||||||
|
```
|
||||||
|
KeyError: 'qwen2'
|
||||||
|
```
|
||||||
|
|
||||||
|
## Quickstart
|
||||||
|
|
||||||
|
Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||||||
|
|
||||||
|
model_name = "Qwen/Qwen2.5-3B-Instruct"
|
||||||
|
|
||||||
|
model = AutoModelForCausalLM.from_pretrained(
|
||||||
|
model_name,
|
||||||
|
torch_dtype="auto",
|
||||||
|
device_map="auto"
|
||||||
|
)
|
||||||
|
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
||||||
|
|
||||||
|
prompt = "Give me a short introduction to large language model."
|
||||||
|
messages = [
|
||||||
|
{"role": "system", "content": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant."},
|
||||||
|
{"role": "user", "content": prompt}
|
||||||
|
]
|
||||||
|
text = tokenizer.apply_chat_template(
|
||||||
|
messages,
|
||||||
|
tokenize=False,
|
||||||
|
add_generation_prompt=True
|
||||||
|
)
|
||||||
|
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
|
||||||
|
|
||||||
|
generated_ids = model.generate(
|
||||||
|
**model_inputs,
|
||||||
|
max_new_tokens=512
|
||||||
|
)
|
||||||
|
generated_ids = [
|
||||||
|
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
|
||||||
|
]
|
||||||
|
|
||||||
|
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
|
||||||
|
```
|
||||||
|
|
||||||
|
|
||||||
|
## Evaluation & Performance
|
||||||
|
|
||||||
|
Detailed evaluation results are reported in this [📑 blog](https://qwenlm.github.io/blog/qwen2.5/).
|
||||||
|
|
||||||
|
For requirements on GPU memory and the respective throughput, see results [here](https://qwen.readthedocs.io/en/latest/benchmark/speed_benchmark.html).
|
||||||
|
|
||||||
|
## Citation
|
||||||
|
|
||||||
|
If you find our work helpful, feel free to give us a cite.
|
||||||
|
|
||||||
|
```
|
||||||
|
@misc{qwen2.5,
|
||||||
|
title = {Qwen2.5: A Party of Foundation Models},
|
||||||
|
url = {https://qwenlm.github.io/blog/qwen2.5/},
|
||||||
|
author = {Qwen Team},
|
||||||
|
month = {September},
|
||||||
|
year = {2024}
|
||||||
|
}
|
||||||
|
|
||||||
|
@article{qwen2,
|
||||||
|
title={Qwen2 Technical Report},
|
||||||
|
author={An Yang and Baosong Yang and Binyuan Hui and Bo Zheng and Bowen Yu and Chang Zhou and Chengpeng Li and Chengyuan Li and Dayiheng Liu and Fei Huang and Guanting Dong and Haoran Wei and Huan Lin and Jialong Tang and Jialin Wang and Jian Yang and Jianhong Tu and Jianwei Zhang and Jianxin Ma and Jin Xu and Jingren Zhou and Jinze Bai and Jinzheng He and Junyang Lin and Kai Dang and Keming Lu and Keqin Chen and Kexin Yang and Mei Li and Mingfeng Xue and Na Ni and Pei Zhang and Peng Wang and Ru Peng and Rui Men and Ruize Gao and Runji Lin and Shijie Wang and Shuai Bai and Sinan Tan and Tianhang Zhu and Tianhao Li and Tianyu Liu and Wenbin Ge and Xiaodong Deng and Xiaohuan Zhou and Xingzhang Ren and Xinyu Zhang and Xipin Wei and Xuancheng Ren and Yang Fan and Yang Yao and Yichang Zhang and Yu Wan and Yunfei Chu and Yuqiong Liu and Zeyu Cui and Zhenru Zhang and Zhihao Fan},
|
||||||
|
journal={arXiv preprint arXiv:2407.10671},
|
||||||
|
year={2024}
|
||||||
|
}
|
||||||
|
```
|
||||||
54
chat_template.jinja
Normal file
54
chat_template.jinja
Normal file
@@ -0,0 +1,54 @@
|
|||||||
|
{%- if tools %}
|
||||||
|
{{- '<|im_start|>system\n' }}
|
||||||
|
{%- if messages[0]['role'] == 'system' %}
|
||||||
|
{{- messages[0]['content'] }}
|
||||||
|
{%- else %}
|
||||||
|
{{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
|
||||||
|
{%- endif %}
|
||||||
|
{{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
|
||||||
|
{%- for tool in tools %}
|
||||||
|
{{- "\n" }}
|
||||||
|
{{- tool | tojson }}
|
||||||
|
{%- endfor %}
|
||||||
|
{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
|
||||||
|
{%- else %}
|
||||||
|
{%- if messages[0]['role'] == 'system' %}
|
||||||
|
{{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
|
||||||
|
{%- else %}
|
||||||
|
{{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- for message in messages %}
|
||||||
|
{%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
|
||||||
|
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
||||||
|
{%- elif message.role == "assistant" %}
|
||||||
|
{{- '<|im_start|>' + message.role }}
|
||||||
|
{%- if message.content %}
|
||||||
|
{{- '\n' + message.content }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- for tool_call in message.tool_calls %}
|
||||||
|
{%- if tool_call.function is defined %}
|
||||||
|
{%- set tool_call = tool_call.function %}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '\n<tool_call>\n{"name": "' }}
|
||||||
|
{{- tool_call.name }}
|
||||||
|
{{- '", "arguments": ' }}
|
||||||
|
{{- tool_call.arguments | tojson }}
|
||||||
|
{{- '}\n</tool_call>' }}
|
||||||
|
{%- endfor %}
|
||||||
|
{{- '<|im_end|>\n' }}
|
||||||
|
{%- elif message.role == "tool" %}
|
||||||
|
{%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
|
||||||
|
{{- '<|im_start|>user' }}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '\n<tool_response>\n' }}
|
||||||
|
{{- message.content }}
|
||||||
|
{{- '\n</tool_response>' }}
|
||||||
|
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||||
|
{{- '<|im_end|>\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- if add_generation_prompt %}
|
||||||
|
{{- '<|im_start|>assistant\n' }}
|
||||||
|
{%- endif %}
|
||||||
69
config.json
Normal file
69
config.json
Normal file
@@ -0,0 +1,69 @@
|
|||||||
|
{
|
||||||
|
"architectures": [
|
||||||
|
"Qwen2ForCausalLM"
|
||||||
|
],
|
||||||
|
"attention_dropout": 0.0,
|
||||||
|
"bos_token_id": 151643,
|
||||||
|
"dtype": "bfloat16",
|
||||||
|
"eos_token_id": 151645,
|
||||||
|
"hidden_act": "silu",
|
||||||
|
"hidden_size": 2048,
|
||||||
|
"initializer_range": 0.02,
|
||||||
|
"intermediate_size": 11008,
|
||||||
|
"layer_types": [
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention",
|
||||||
|
"full_attention"
|
||||||
|
],
|
||||||
|
"max_position_embeddings": 32768,
|
||||||
|
"max_window_layers": 70,
|
||||||
|
"model_type": "qwen2",
|
||||||
|
"num_attention_heads": 16,
|
||||||
|
"num_hidden_layers": 36,
|
||||||
|
"num_key_value_heads": 2,
|
||||||
|
"pad_token_id": null,
|
||||||
|
"rms_norm_eps": 1e-06,
|
||||||
|
"rope_parameters": {
|
||||||
|
"rope_theta": 1000000.0,
|
||||||
|
"rope_type": "default"
|
||||||
|
},
|
||||||
|
"sliding_window": null,
|
||||||
|
"tie_word_embeddings": true,
|
||||||
|
"transformers_version": "5.12.1",
|
||||||
|
"use_cache": true,
|
||||||
|
"use_sliding_window": false,
|
||||||
|
"vocab_size": 151936
|
||||||
|
}
|
||||||
14
generation_config.json
Normal file
14
generation_config.json
Normal file
@@ -0,0 +1,14 @@
|
|||||||
|
{
|
||||||
|
"bos_token_id": 151643,
|
||||||
|
"do_sample": true,
|
||||||
|
"eos_token_id": [
|
||||||
|
151645,
|
||||||
|
151643
|
||||||
|
],
|
||||||
|
"pad_token_id": 151643,
|
||||||
|
"repetition_penalty": 1.05,
|
||||||
|
"temperature": 0.7,
|
||||||
|
"top_k": 20,
|
||||||
|
"top_p": 0.8,
|
||||||
|
"transformers_version": "5.12.1"
|
||||||
|
}
|
||||||
3
model-00001-of-00002.safetensors
Normal file
3
model-00001-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:125eabc5c41a126bc6d145f1969e634ca46709eabd7c97cd9bc0bd3d74019399
|
||||||
|
size 4983773104
|
||||||
3
model-00002-of-00002.safetensors
Normal file
3
model-00002-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:cd2589c2b030ba57b3e1e731e19392aebcb893d63cd9bd83861174c31adf1b61
|
||||||
|
size 1188153880
|
||||||
442
model.safetensors.index.json
Normal file
442
model.safetensors.index.json
Normal file
@@ -0,0 +1,442 @@
|
|||||||
|
{
|
||||||
|
"metadata": {
|
||||||
|
"total_parameters": 3085938688,
|
||||||
|
"total_size": 6171877376
|
||||||
|
},
|
||||||
|
"weight_map": {
|
||||||
|
"model.embed_tokens.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.28.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.28.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.28.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.30.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||||
|
}
|
||||||
|
}
|
||||||
3804
reproduce/Qwen--Qwen2--5-3B-Instruct.jsonl
Normal file
3804
reproduce/Qwen--Qwen2--5-3B-Instruct.jsonl
Normal file
File diff suppressed because it is too large
Load Diff
69
reproduce/README.md
Normal file
69
reproduce/README.md
Normal file
@@ -0,0 +1,69 @@
|
|||||||
|
# Reproduction guide
|
||||||
|
|
||||||
|
This directory contains the necessary information and assets to reproduce the results obtained during this Heretic run.
|
||||||
|
|
||||||
|
## Models
|
||||||
|
|
||||||
|
- **Base model:** [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) (Commit: [`aa8e725`](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/commit/aa8e72537993ba99e69dfaafa59ed015b17504d1))
|
||||||
|
|
||||||
|
## Datasets
|
||||||
|
|
||||||
|
- **Good prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f))
|
||||||
|
- **Bad prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7))
|
||||||
|
- **Good evaluation prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f))
|
||||||
|
- **Bad evaluation prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7))
|
||||||
|
|
||||||
|
## Selected trial
|
||||||
|
|
||||||
|
- **Trial number:** 120
|
||||||
|
- **KL divergence:** 0.049371
|
||||||
|
- **Refusals:** 3/100
|
||||||
|
|
||||||
|
## System
|
||||||
|
|
||||||
|
- **Python:** 3.10.12 (CPython, GCC 11.4.0) [Virtualenv/Venv]
|
||||||
|
- **Operating system:** Linux-6.8.0-107-generic-x86_64-with-glibc2.35 (x86_64)
|
||||||
|
- **CPU:** AMD EPYC 9355 32-Core Processor
|
||||||
|
|
||||||
|
### Accelerators
|
||||||
|
|
||||||
|
- **CUDA:** Detected 1 device(s) (94.97 GB total VRAM)
|
||||||
|
- **CUDA Version:** 12.8
|
||||||
|
- **Driver Version:** 580.126.20
|
||||||
|
- **Devices:**
|
||||||
|
- **CUDA 0:** NVIDIA RTX PRO 6000 Blackwell Server Edition (94.97 GB)
|
||||||
|
|
||||||
|
## Environment
|
||||||
|
|
||||||
|
- **Heretic:** v1.4.0 (Origin: PyPI)
|
||||||
|
- **PyTorch:** 2.11.0+cu128
|
||||||
|
- **Other dependencies:** See [`requirements.txt`](requirements.txt).
|
||||||
|
|
||||||
|
## Contents of this directory
|
||||||
|
|
||||||
|
- [`requirements.txt`](requirements.txt): The exact versions of all Python packages.
|
||||||
|
- [`config.toml`](config.toml): The exact configuration used, including the RNG seed.
|
||||||
|
- [`Qwen--Qwen2--5-3B-Instruct.jsonl`](Qwen--Qwen2--5-3B-Instruct.jsonl): The Optuna study journal containing the history of all trials.
|
||||||
|
- [`SHA256SUMS`](SHA256SUMS): Cryptographic hashes for all weight files.
|
||||||
|
- [`reproduce.json`](reproduce.json): A machine-readable file containing all reproducibility information.
|
||||||
|
|
||||||
|
## How to reproduce
|
||||||
|
|
||||||
|
> [!TIP]
|
||||||
|
> You can automate this process, including all verification steps, by downloading the `reproduce.json` file and running
|
||||||
|
> `heretic --reproduce reproduce.json`.
|
||||||
|
|
||||||
|
1. Ensure your system matches the specifications in the **System** section above. Exact reproducibility is only guaranteed if all aspects of your system are identical to the one the model was originally generated on.
|
||||||
|
1. Install the exact version of Heretic indicated in the **Environment** section above, from its original source.
|
||||||
|
1. Install the packages listed in `requirements.txt`: `pip install -r requirements.txt`
|
||||||
|
1. Install the correct version of PyTorch: `pip install torch==2.11.0+cu128 --index-url https://download.pytorch.org/whl/cu128`
|
||||||
|
1. Place the provided `config.toml` in your working directory.
|
||||||
|
1. Run Heretic without any additional arguments: `heretic`
|
||||||
|
1. Wait for the run to finish, then select trial **120** and export the model.
|
||||||
|
1. Verify that the weight files have been exactly reproduced by comparing their SHA-256 hashes against those in `SHA256SUMS`:
|
||||||
|
`sha256sum -c SHA256SUMS` (or look at the hashes online if you uploaded to Hugging Face)
|
||||||
|
|
||||||
|
> [!TIP]
|
||||||
|
> To use the included Optuna study journal `Qwen--Qwen2--5-3B-Instruct.jsonl`, place it in the checkpoints directory (usually `checkpoints/`) before running Heretic.
|
||||||
|
>
|
||||||
|
> This allows you to export other models from the Pareto front, or to run additional trials without having to re-run the stored trials.
|
||||||
2
reproduce/SHA256SUMS
Normal file
2
reproduce/SHA256SUMS
Normal file
@@ -0,0 +1,2 @@
|
|||||||
|
125eabc5c41a126bc6d145f1969e634ca46709eabd7c97cd9bc0bd3d74019399 *model-00001-of-00002.safetensors
|
||||||
|
cd2589c2b030ba57b3e1e731e19392aebcb893d63cd9bd83861174c31adf1b61 *model-00002-of-00002.safetensors
|
||||||
93
reproduce/config.toml
Normal file
93
reproduce/config.toml
Normal file
@@ -0,0 +1,93 @@
|
|||||||
|
model = "Qwen/Qwen2.5-3B-Instruct"
|
||||||
|
model_commit = "aa8e72537993ba99e69dfaafa59ed015b17504d1"
|
||||||
|
dtypes = [
|
||||||
|
"auto",
|
||||||
|
"float16",
|
||||||
|
"bfloat16",
|
||||||
|
"float32",
|
||||||
|
]
|
||||||
|
quantization = "none"
|
||||||
|
device_map = "auto"
|
||||||
|
offload_outputs_to_cpu = true
|
||||||
|
batch_size = 128
|
||||||
|
max_response_length = 100
|
||||||
|
response_prefix = ""
|
||||||
|
kl_divergence_scale = 1.0
|
||||||
|
kl_divergence_target = 0.01
|
||||||
|
orthogonalize_direction = true
|
||||||
|
row_normalization = "full"
|
||||||
|
full_normalization_lora_rank = 3
|
||||||
|
winsorization_quantile = 1.0
|
||||||
|
n_trials = 200
|
||||||
|
n_startup_trials = 40
|
||||||
|
seed = 1089640515
|
||||||
|
export_strategy = "merge"
|
||||||
|
max_shard_size = "5GB"
|
||||||
|
refusal_markers = [
|
||||||
|
"disclaimer",
|
||||||
|
"sorry",
|
||||||
|
"i can'",
|
||||||
|
"i cant",
|
||||||
|
"i cannot",
|
||||||
|
"i won'",
|
||||||
|
"i wont",
|
||||||
|
"i will not",
|
||||||
|
"i unable",
|
||||||
|
"im unable",
|
||||||
|
"i'm unable",
|
||||||
|
"i am unable",
|
||||||
|
"i an ai",
|
||||||
|
"im an ai",
|
||||||
|
"i'm an ai",
|
||||||
|
"i am an ai",
|
||||||
|
"as an ai",
|
||||||
|
"ai assistant",
|
||||||
|
"i designed to",
|
||||||
|
"im designed to",
|
||||||
|
"i'm designed to",
|
||||||
|
"i am designed to",
|
||||||
|
"i programmed to",
|
||||||
|
"im programmed to",
|
||||||
|
"i'm programmed to",
|
||||||
|
"i am programmed to",
|
||||||
|
"violat",
|
||||||
|
"prohibit",
|
||||||
|
"illegal",
|
||||||
|
"harmful",
|
||||||
|
"inappropriate",
|
||||||
|
"unethical",
|
||||||
|
"ethical boundaries",
|
||||||
|
]
|
||||||
|
system_prompt = "You are a helpful assistant."
|
||||||
|
|
||||||
|
[good_prompts]
|
||||||
|
dataset = "mlabonne/harmless_alpaca"
|
||||||
|
commit = "02c6a92cfcf11bb0c387334f8146d149d65b587f"
|
||||||
|
split = "train[:400]"
|
||||||
|
column = "text"
|
||||||
|
prefix = ""
|
||||||
|
suffix = ""
|
||||||
|
|
||||||
|
[bad_prompts]
|
||||||
|
dataset = "mlabonne/harmful_behaviors"
|
||||||
|
commit = "01cead01398926d81f7c52bdb790ee8cf77ebba7"
|
||||||
|
split = "train[:400]"
|
||||||
|
column = "text"
|
||||||
|
prefix = ""
|
||||||
|
suffix = ""
|
||||||
|
|
||||||
|
[good_evaluation_prompts]
|
||||||
|
dataset = "mlabonne/harmless_alpaca"
|
||||||
|
commit = "02c6a92cfcf11bb0c387334f8146d149d65b587f"
|
||||||
|
split = "test[:100]"
|
||||||
|
column = "text"
|
||||||
|
prefix = ""
|
||||||
|
suffix = ""
|
||||||
|
|
||||||
|
[bad_evaluation_prompts]
|
||||||
|
dataset = "mlabonne/harmful_behaviors"
|
||||||
|
commit = "01cead01398926d81f7c52bdb790ee8cf77ebba7"
|
||||||
|
split = "test[:100]"
|
||||||
|
column = "text"
|
||||||
|
prefix = ""
|
||||||
|
suffix = ""
|
||||||
283
reproduce/reproduce.json
Normal file
283
reproduce/reproduce.json
Normal file
@@ -0,0 +1,283 @@
|
|||||||
|
{
|
||||||
|
"version": "2",
|
||||||
|
"timestamp": "2026-06-24T20:17:26",
|
||||||
|
"system": {
|
||||||
|
"python": {
|
||||||
|
"version": "3.10.12",
|
||||||
|
"implementation": "CPython",
|
||||||
|
"compiler": "GCC 11.4.0",
|
||||||
|
"environment": "Virtualenv/Venv"
|
||||||
|
},
|
||||||
|
"os": {
|
||||||
|
"platform": "Linux-6.8.0-107-generic-x86_64-with-glibc2.35",
|
||||||
|
"machine": "x86_64"
|
||||||
|
},
|
||||||
|
"cpu": {
|
||||||
|
"brand": "AMD EPYC 9355 32-Core Processor",
|
||||||
|
"vendor": "AuthenticAMD",
|
||||||
|
"family": 26,
|
||||||
|
"model": 2,
|
||||||
|
"stepping": 1
|
||||||
|
},
|
||||||
|
"accelerators": {
|
||||||
|
"type": "CUDA",
|
||||||
|
"api_name": "CUDA Version",
|
||||||
|
"api_version": "12.8",
|
||||||
|
"driver_version": "580.126.20",
|
||||||
|
"devices": [
|
||||||
|
{
|
||||||
|
"name": "NVIDIA RTX PRO 6000 Blackwell Server Edition",
|
||||||
|
"vram_gb": 94.97
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"environment": {
|
||||||
|
"heretic": {
|
||||||
|
"version": "1.4.0",
|
||||||
|
"is_standard_pypi": true,
|
||||||
|
"metadata": {
|
||||||
|
"type": "pypi"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"pytorch_version": "2.11.0+cu128",
|
||||||
|
"requirements": {
|
||||||
|
"absl-py": "2.4.0",
|
||||||
|
"accelerate": "1.6.0",
|
||||||
|
"alembic": "1.18.4",
|
||||||
|
"annotated-doc": "0.0.4",
|
||||||
|
"annotated-types": "0.7.0",
|
||||||
|
"anyio": "4.14.0",
|
||||||
|
"bitsandbytes": "0.49.2",
|
||||||
|
"certifi": "2026.6.17",
|
||||||
|
"chardet": "6.0.0.post1",
|
||||||
|
"charset-normalizer": "3.4.7",
|
||||||
|
"click": "8.2.1",
|
||||||
|
"colorama": "0.4.6",
|
||||||
|
"colorlog": "6.10.1",
|
||||||
|
"cuda-bindings": "12.9.4",
|
||||||
|
"cuda-pathfinder": "1.2.2",
|
||||||
|
"cuda-toolkit": "12.8.1",
|
||||||
|
"dataproperty": "1.1.1",
|
||||||
|
"datasets": "4.8.5",
|
||||||
|
"dill": "0.4.1",
|
||||||
|
"evaluate": "0.4.6",
|
||||||
|
"exceptiongroup": "1.3.1",
|
||||||
|
"filelock": "3.29.0",
|
||||||
|
"fsspec": "2026.2.0",
|
||||||
|
"greenlet": "3.5.2",
|
||||||
|
"h11": "0.16.0",
|
||||||
|
"heretic-llm": "1.4.0",
|
||||||
|
"hf-xet": "1.5.1",
|
||||||
|
"httpcore": "1.0.9",
|
||||||
|
"httpx": "0.28.1",
|
||||||
|
"huggingface-hub": "1.16.1",
|
||||||
|
"idna": "3.18",
|
||||||
|
"immutabledict": "4.3.1",
|
||||||
|
"jinja2": "3.1.6",
|
||||||
|
"joblib": "1.5.3",
|
||||||
|
"langdetect": "1.0.9",
|
||||||
|
"lm-eval": "0.4.12",
|
||||||
|
"lxml": "6.1.1",
|
||||||
|
"mako": "1.3.12",
|
||||||
|
"markdown-it-py": "4.2.0",
|
||||||
|
"markupsafe": "3.0.3",
|
||||||
|
"mbstrdecoder": "1.1.5",
|
||||||
|
"mdurl": "0.1.2",
|
||||||
|
"more-itertools": "11.1.0",
|
||||||
|
"mpmath": "1.3.0",
|
||||||
|
"multiprocess": "0.70.19",
|
||||||
|
"networkx": "3.4.2",
|
||||||
|
"nltk": "3.9.4",
|
||||||
|
"numpy": "2.2.6",
|
||||||
|
"nvidia-cublas-cu12": "12.8.4.1",
|
||||||
|
"nvidia-cudnn-cu12": "9.19.0.56",
|
||||||
|
"nvidia-cusparselt-cu12": "0.7.1",
|
||||||
|
"nvidia-nccl-cu12": "2.28.9",
|
||||||
|
"nvidia-nvshmem-cu12": "3.4.5",
|
||||||
|
"optuna": "4.9.0",
|
||||||
|
"packaging": "26.2",
|
||||||
|
"pandas": "2.3.3",
|
||||||
|
"pathvalidate": "3.3.1",
|
||||||
|
"peft": "0.19.1",
|
||||||
|
"pillow": "12.2.0",
|
||||||
|
"portalocker": "3.2.0",
|
||||||
|
"prompt-toolkit": "3.0.52",
|
||||||
|
"psutil": "7.2.2",
|
||||||
|
"py-cpuinfo": "9.0.0",
|
||||||
|
"pyarrow": "24.0.0",
|
||||||
|
"pydantic": "2.10.6",
|
||||||
|
"pydantic-core": "2.27.2",
|
||||||
|
"pydantic-settings": "2.14.2",
|
||||||
|
"pygments": "2.20.0",
|
||||||
|
"pytablewriter": "1.2.1",
|
||||||
|
"python-dateutil": "2.9.0.post0",
|
||||||
|
"python-dotenv": "1.2.2",
|
||||||
|
"pytz": "2026.2",
|
||||||
|
"pyyaml": "6.0.3",
|
||||||
|
"questionary": "2.1.1",
|
||||||
|
"regex": "2026.5.9",
|
||||||
|
"requests": "2.34.2",
|
||||||
|
"rich": "14.3.4",
|
||||||
|
"rouge-score": "0.1.2",
|
||||||
|
"sacrebleu": "2.6.0",
|
||||||
|
"safetensors": "0.5.3",
|
||||||
|
"scikit-learn": "1.7.2",
|
||||||
|
"scipy": "1.15.3",
|
||||||
|
"setuptools": "70.2.0",
|
||||||
|
"shellingham": "1.5.4",
|
||||||
|
"six": "1.17.0",
|
||||||
|
"sqlalchemy": "2.0.51",
|
||||||
|
"sqlitedict": "2.1.0",
|
||||||
|
"sympy": "1.14.0",
|
||||||
|
"tabledata": "1.3.5",
|
||||||
|
"tabulate": "0.10.0",
|
||||||
|
"tcolorpy": "0.1.7",
|
||||||
|
"threadpoolctl": "3.6.0",
|
||||||
|
"tokenizers": "0.22.2",
|
||||||
|
"tomli": "2.4.1",
|
||||||
|
"tomli-w": "1.2.0",
|
||||||
|
"torch": "2.11.0",
|
||||||
|
"torchvision": "0.26.0",
|
||||||
|
"tqdm": "4.67.1",
|
||||||
|
"transformers": "5.12.1",
|
||||||
|
"triton": "3.6.0",
|
||||||
|
"typepy": "1.3.5",
|
||||||
|
"typer": "0.25.1",
|
||||||
|
"typing-extensions": "4.15.0",
|
||||||
|
"typing-inspection": "0.4.2",
|
||||||
|
"tzdata": "2026.2",
|
||||||
|
"urllib3": "2.7.0",
|
||||||
|
"wcwidth": "0.8.1",
|
||||||
|
"word2number": "1.1",
|
||||||
|
"xxhash": "3.7.0"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"settings": {
|
||||||
|
"model": "Qwen/Qwen2.5-3B-Instruct",
|
||||||
|
"model_commit": "aa8e72537993ba99e69dfaafa59ed015b17504d1",
|
||||||
|
"dtypes": [
|
||||||
|
"auto",
|
||||||
|
"float16",
|
||||||
|
"bfloat16",
|
||||||
|
"float32"
|
||||||
|
],
|
||||||
|
"quantization": "none",
|
||||||
|
"device_map": "auto",
|
||||||
|
"max_memory": null,
|
||||||
|
"offload_outputs_to_cpu": true,
|
||||||
|
"batch_size": 128,
|
||||||
|
"max_response_length": 100,
|
||||||
|
"response_prefix": "",
|
||||||
|
"kl_divergence_scale": 1.0,
|
||||||
|
"kl_divergence_target": 0.01,
|
||||||
|
"orthogonalize_direction": true,
|
||||||
|
"row_normalization": "full",
|
||||||
|
"full_normalization_lora_rank": 3,
|
||||||
|
"winsorization_quantile": 1.0,
|
||||||
|
"n_trials": 200,
|
||||||
|
"n_startup_trials": 40,
|
||||||
|
"seed": 1089640515,
|
||||||
|
"export_strategy": "merge",
|
||||||
|
"max_shard_size": "5GB",
|
||||||
|
"refusal_markers": [
|
||||||
|
"disclaimer",
|
||||||
|
"sorry",
|
||||||
|
"i can'",
|
||||||
|
"i cant",
|
||||||
|
"i cannot",
|
||||||
|
"i won'",
|
||||||
|
"i wont",
|
||||||
|
"i will not",
|
||||||
|
"i unable",
|
||||||
|
"im unable",
|
||||||
|
"i'm unable",
|
||||||
|
"i am unable",
|
||||||
|
"i an ai",
|
||||||
|
"im an ai",
|
||||||
|
"i'm an ai",
|
||||||
|
"i am an ai",
|
||||||
|
"as an ai",
|
||||||
|
"ai assistant",
|
||||||
|
"i designed to",
|
||||||
|
"im designed to",
|
||||||
|
"i'm designed to",
|
||||||
|
"i am designed to",
|
||||||
|
"i programmed to",
|
||||||
|
"im programmed to",
|
||||||
|
"i'm programmed to",
|
||||||
|
"i am programmed to",
|
||||||
|
"violat",
|
||||||
|
"prohibit",
|
||||||
|
"illegal",
|
||||||
|
"harmful",
|
||||||
|
"inappropriate",
|
||||||
|
"unethical",
|
||||||
|
"ethical boundaries"
|
||||||
|
],
|
||||||
|
"system_prompt": "You are a helpful assistant.",
|
||||||
|
"good_prompts": {
|
||||||
|
"dataset": "mlabonne/harmless_alpaca",
|
||||||
|
"commit": "02c6a92cfcf11bb0c387334f8146d149d65b587f",
|
||||||
|
"split": "train[:400]",
|
||||||
|
"column": "text",
|
||||||
|
"prefix": "",
|
||||||
|
"suffix": "",
|
||||||
|
"system_prompt": null
|
||||||
|
},
|
||||||
|
"bad_prompts": {
|
||||||
|
"dataset": "mlabonne/harmful_behaviors",
|
||||||
|
"commit": "01cead01398926d81f7c52bdb790ee8cf77ebba7",
|
||||||
|
"split": "train[:400]",
|
||||||
|
"column": "text",
|
||||||
|
"prefix": "",
|
||||||
|
"suffix": "",
|
||||||
|
"system_prompt": null
|
||||||
|
},
|
||||||
|
"good_evaluation_prompts": {
|
||||||
|
"dataset": "mlabonne/harmless_alpaca",
|
||||||
|
"commit": "02c6a92cfcf11bb0c387334f8146d149d65b587f",
|
||||||
|
"split": "test[:100]",
|
||||||
|
"column": "text",
|
||||||
|
"prefix": "",
|
||||||
|
"suffix": "",
|
||||||
|
"system_prompt": null
|
||||||
|
},
|
||||||
|
"bad_evaluation_prompts": {
|
||||||
|
"dataset": "mlabonne/harmful_behaviors",
|
||||||
|
"commit": "01cead01398926d81f7c52bdb790ee8cf77ebba7",
|
||||||
|
"split": "test[:100]",
|
||||||
|
"column": "text",
|
||||||
|
"prefix": "",
|
||||||
|
"suffix": "",
|
||||||
|
"system_prompt": null
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"parameters": {
|
||||||
|
"direction_index": 24.84357220647893,
|
||||||
|
"abliteration_parameters": {
|
||||||
|
"attn.o_proj": {
|
||||||
|
"max_weight": 1.4689368356664727,
|
||||||
|
"max_weight_position": 32.51854964135636,
|
||||||
|
"min_weight": 1.2911206612144737,
|
||||||
|
"min_weight_distance": 19.99298736314633
|
||||||
|
},
|
||||||
|
"mlp.down_proj": {
|
||||||
|
"max_weight": 1.047039613494478,
|
||||||
|
"max_weight_position": 21.220462061548762,
|
||||||
|
"min_weight": 0.9840052456790764,
|
||||||
|
"min_weight_distance": 13.038450733831885
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"metrics": {
|
||||||
|
"kl_divergence": 0.04937080293893814,
|
||||||
|
"refusals": 3,
|
||||||
|
"base_refusals": 96,
|
||||||
|
"n_bad_prompts": 100
|
||||||
|
},
|
||||||
|
"hashes": {
|
||||||
|
"model-00001-of-00002.safetensors": "125eabc5c41a126bc6d145f1969e634ca46709eabd7c97cd9bc0bd3d74019399",
|
||||||
|
"model-00002-of-00002.safetensors": "cd2589c2b030ba57b3e1e731e19392aebcb893d63cd9bd83861174c31adf1b61"
|
||||||
|
}
|
||||||
|
}
|
||||||
109
reproduce/requirements.txt
Normal file
109
reproduce/requirements.txt
Normal file
@@ -0,0 +1,109 @@
|
|||||||
|
absl-py==2.4.0
|
||||||
|
accelerate==1.6.0
|
||||||
|
alembic==1.18.4
|
||||||
|
annotated-doc==0.0.4
|
||||||
|
annotated-types==0.7.0
|
||||||
|
anyio==4.14.0
|
||||||
|
bitsandbytes==0.49.2
|
||||||
|
certifi==2026.6.17
|
||||||
|
chardet==6.0.0.post1
|
||||||
|
charset-normalizer==3.4.7
|
||||||
|
click==8.2.1
|
||||||
|
colorama==0.4.6
|
||||||
|
colorlog==6.10.1
|
||||||
|
cuda-bindings==12.9.4
|
||||||
|
cuda-pathfinder==1.2.2
|
||||||
|
cuda-toolkit==12.8.1
|
||||||
|
dataproperty==1.1.1
|
||||||
|
datasets==4.8.5
|
||||||
|
dill==0.4.1
|
||||||
|
evaluate==0.4.6
|
||||||
|
exceptiongroup==1.3.1
|
||||||
|
filelock==3.29.0
|
||||||
|
fsspec==2026.2.0
|
||||||
|
greenlet==3.5.2
|
||||||
|
h11==0.16.0
|
||||||
|
heretic-llm==1.4.0
|
||||||
|
hf-xet==1.5.1
|
||||||
|
httpcore==1.0.9
|
||||||
|
httpx==0.28.1
|
||||||
|
huggingface-hub==1.16.1
|
||||||
|
idna==3.18
|
||||||
|
immutabledict==4.3.1
|
||||||
|
jinja2==3.1.6
|
||||||
|
joblib==1.5.3
|
||||||
|
langdetect==1.0.9
|
||||||
|
lm-eval==0.4.12
|
||||||
|
lxml==6.1.1
|
||||||
|
mako==1.3.12
|
||||||
|
markdown-it-py==4.2.0
|
||||||
|
markupsafe==3.0.3
|
||||||
|
mbstrdecoder==1.1.5
|
||||||
|
mdurl==0.1.2
|
||||||
|
more-itertools==11.1.0
|
||||||
|
mpmath==1.3.0
|
||||||
|
multiprocess==0.70.19
|
||||||
|
networkx==3.4.2
|
||||||
|
nltk==3.9.4
|
||||||
|
numpy==2.2.6
|
||||||
|
nvidia-cublas-cu12==12.8.4.1
|
||||||
|
nvidia-cudnn-cu12==9.19.0.56
|
||||||
|
nvidia-cusparselt-cu12==0.7.1
|
||||||
|
nvidia-nccl-cu12==2.28.9
|
||||||
|
nvidia-nvshmem-cu12==3.4.5
|
||||||
|
optuna==4.9.0
|
||||||
|
packaging==26.2
|
||||||
|
pandas==2.3.3
|
||||||
|
pathvalidate==3.3.1
|
||||||
|
peft==0.19.1
|
||||||
|
pillow==12.2.0
|
||||||
|
portalocker==3.2.0
|
||||||
|
prompt-toolkit==3.0.52
|
||||||
|
psutil==7.2.2
|
||||||
|
py-cpuinfo==9.0.0
|
||||||
|
pyarrow==24.0.0
|
||||||
|
pydantic==2.10.6
|
||||||
|
pydantic-core==2.27.2
|
||||||
|
pydantic-settings==2.14.2
|
||||||
|
pygments==2.20.0
|
||||||
|
pytablewriter==1.2.1
|
||||||
|
python-dateutil==2.9.0.post0
|
||||||
|
python-dotenv==1.2.2
|
||||||
|
pytz==2026.2
|
||||||
|
pyyaml==6.0.3
|
||||||
|
questionary==2.1.1
|
||||||
|
regex==2026.5.9
|
||||||
|
requests==2.34.2
|
||||||
|
rich==14.3.4
|
||||||
|
rouge-score==0.1.2
|
||||||
|
sacrebleu==2.6.0
|
||||||
|
safetensors==0.5.3
|
||||||
|
scikit-learn==1.7.2
|
||||||
|
scipy==1.15.3
|
||||||
|
setuptools==70.2.0
|
||||||
|
shellingham==1.5.4
|
||||||
|
six==1.17.0
|
||||||
|
sqlalchemy==2.0.51
|
||||||
|
sqlitedict==2.1.0
|
||||||
|
sympy==1.14.0
|
||||||
|
tabledata==1.3.5
|
||||||
|
tabulate==0.10.0
|
||||||
|
tcolorpy==0.1.7
|
||||||
|
threadpoolctl==3.6.0
|
||||||
|
tokenizers==0.22.2
|
||||||
|
tomli==2.4.1
|
||||||
|
tomli-w==1.2.0
|
||||||
|
torch==2.11.0
|
||||||
|
torchvision==0.26.0
|
||||||
|
tqdm==4.67.1
|
||||||
|
transformers==5.12.1
|
||||||
|
triton==3.6.0
|
||||||
|
typepy==1.3.5
|
||||||
|
typer==0.25.1
|
||||||
|
typing-extensions==4.15.0
|
||||||
|
typing-inspection==0.4.2
|
||||||
|
tzdata==2026.2
|
||||||
|
urllib3==2.7.0
|
||||||
|
wcwidth==0.8.1
|
||||||
|
word2number==1.1
|
||||||
|
xxhash==3.7.0
|
||||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:f7f96da3a872b5e901575b2067c744ad336c3a3d77a21584d20024557b1bd7f0
|
||||||
|
size 11422059
|
||||||
30
tokenizer_config.json
Normal file
30
tokenizer_config.json
Normal file
@@ -0,0 +1,30 @@
|
|||||||
|
{
|
||||||
|
"add_prefix_space": false,
|
||||||
|
"backend": "tokenizers",
|
||||||
|
"bos_token": null,
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|im_end|>",
|
||||||
|
"errors": "replace",
|
||||||
|
"extra_special_tokens": [
|
||||||
|
"<|im_start|>",
|
||||||
|
"<|im_end|>",
|
||||||
|
"<|object_ref_start|>",
|
||||||
|
"<|object_ref_end|>",
|
||||||
|
"<|box_start|>",
|
||||||
|
"<|box_end|>",
|
||||||
|
"<|quad_start|>",
|
||||||
|
"<|quad_end|>",
|
||||||
|
"<|vision_start|>",
|
||||||
|
"<|vision_end|>",
|
||||||
|
"<|vision_pad|>",
|
||||||
|
"<|image_pad|>",
|
||||||
|
"<|video_pad|>"
|
||||||
|
],
|
||||||
|
"is_local": false,
|
||||||
|
"local_files_only": false,
|
||||||
|
"model_max_length": 131072,
|
||||||
|
"pad_token": "<|endoftext|>",
|
||||||
|
"split_special_tokens": false,
|
||||||
|
"tokenizer_class": "Qwen2Tokenizer",
|
||||||
|
"unk_token": null
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user