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Model: ISTA-MLCV/Llama_3.1_8b_single_emb Source: Original Platform
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README.md
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README.md
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---
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library_name: transformers
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tags: []
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---
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# Llama 3.1 8B Vanilla
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This is the [**Llama 3.1 8B**](https://huggingface.co/meta-llama/Llama-3.1-8B) model fine-tuned as the vanilla (unmodified) baseline, trained and evaluated in the paper [ASIDE: Architectural Separation of Instructions and Data in Language Models](https://openreview.net/forum?id=C81TnwHiRM).
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## Model Description
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This is the vanilla (unmodified) baseline fine-tuned with the same training data and procedure, but without any embedding modification.
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## Usage
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To use this model, first clone and follow the installation instructions in the official [ASIDE Repository](https://github.com/egozverev/aside/tree/main).
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Inside the repository, run the following code snippet [(also provided here as a script)](https://github.com/egozverev/aside/blob/main/experiments/example.py) to do inference with this model.
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```python
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import torch
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import deepspeed
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import json
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import os
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from huggingface_hub import login
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from model_api import CustomModelHandler # Import your custom handler
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from model_api import format_prompt # Import your prompt formatting function
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# Define your instruction and data
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instruction_text = "Translate to German."
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data_text = "Who is Albert Einstein?"
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# Model configuration
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hf_token = os.environ["HUGGINGFACE_HUB_TOKEN"]
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login(token=hf_token)
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embedding_type = "single_emb"
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base_model = "meta-llama/Llama-3.1-8B"
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model_path = "Embeddings-Collab/llama_3.1_8b_single_emb_emb_SFTv110_from_base_run_11_fix"
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# Initialize the model handler
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handler = CustomModelHandler(
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model_path,
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base_model,
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base_model,
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model_path,
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None,
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0,
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embedding_type=embedding_type,
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load_from_checkpoint=True
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)
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# Initialize DeepSpeed inference engine
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engine = deepspeed.init_inference(
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model=handler.model,
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mp_size=torch.cuda.device_count(), # Number of GPUs
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dtype=torch.float16,
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replace_method='auto',
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replace_with_kernel_inject=False
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)
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handler.model = engine.module
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# Load prompt templates
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with open("./data/prompt_templates.json", "r") as f:
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templates = json.load(f)
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template = templates[0]
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instruction_text = format_prompt(instruction_text, template, "system")
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data_text = format_prompt(data_text, template, "user")
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# Generate output
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output, inp = handler.call_model_api_batch([instruction_text], [data_text])
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print(output)
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```
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### Citation
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If you use this model, please cite our paper:
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```
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@inproceedings{
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zverev2026aside,
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title={{ASIDE}}: Architectural Separation of Instructions and Data in Language Models},
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author={Egor Zverev and Evgenii Kortukov and Alexander Panfilov and Alexandra Volkova and Rush Tabesh and Sebastian Lapuschkin and Wojciech Samek and Christoph H. Lampert},
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booktitle={The Fourteenth International Conference on Learning Representations},
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year={2026},
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url={https://openreview.net/forum?id=C81TnwHiRM}
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}
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```
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config.json
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{
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"_name_or_path": "./models/llama_3.1_8b/pretrained_vanilla/train_checkpoints/SFTv110/from_base_run_11_fix/last",
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"add_linear_shift": null,
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128009,
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"gradual_rotation": null,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"learned_rotation": null,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pad_token_id": 128011,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"rotation_alpha": null,
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"rotation_direction": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.47.1",
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"use_cache": false,
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"vocab_size": 128256
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}
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generation_config.json
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"_from_model_config": true,
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"bos_token_id": 128000,
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"do_sample": true,
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"eos_token_id": 128001,
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.47.1"
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}
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|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|reserved_special_token_3|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:80987e597993a6de0093b23341a1ebf40c178a7eee2a921f96f308807e17d73d
|
||||
size 17210200
|
||||
2071
tokenizer_config.json
Normal file
2071
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user