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Model: westenfelder/Llama-3.1-8B-Instruct-NL2SH Source: Original Platform
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---
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library_name: transformers
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pipeline_tag: translation
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license: mit
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datasets:
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- westenfelder/NL2SH-ALFA
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language:
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- en
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base_model: meta-llama/Llama-3.1-8B-Instruct
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model-index:
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- name: Llama-3.1-8B-Instruct-NL2SH
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results:
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- task:
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type: translation
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name: Natural Language to Bash Translation
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dataset:
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type: translation
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name: NL2SH-ALFA
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split: test
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metrics:
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- type: accuracy
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value: 0.40
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name: InterCode-ALFA
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source:
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name: InterCode-ALFA
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url: https://arxiv.org/abs/2502.06858
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---
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# Model Card for Llama-3.1-8B-Instruct-NL2SH
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This model translates natural language (English) instructions to Bash commands.
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## Model Details
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### Model Description
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This model is a fine-tuned version of the [Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) model trained on the [NL2SH-ALFA](https://huggingface.co/datasets/westenfelder/NL2SH-ALFA) dataset for the task of natural language to Bash translation (NL2SH). For more information, please refer to the [paper](https://arxiv.org/abs/2502.06858).
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- **Developed by:** [Anyscale Learning For All (ALFA) Group at MIT-CSAIL](https://alfagroup.csail.mit.edu/)
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- **Language:** English
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- **License:** MIT License
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- **Finetuned from model:** [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)
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### Model Sources
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- **Repository:** [GitHub Repo](https://github.com/westenfelder/NL2SH)
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- **Paper:** [LLM-Supported Natural Language to Bash Translation](https://arxiv.org/abs/2502.06858)
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## Uses
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### Direct Use
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This model is intended for research on machine translation. The model can also be used as an educational resource for learning Bash.
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### Out-of-Scope Use
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This model should not be used in production or automated systems without human verification.
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**Considerations for use in high-risk environments:** This model should not be used in high-risk environments due to its low accuracy and potential for generating harmful commands.
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## Bias, Risks, and Limitations
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This model has a tendency to generate overly complex and incorrect Bash commands. It may produce harmful commands that delete data or corrupt a system. This model is not intended for natural languages other than English, scripting languages or than Bash, or multi-line Bash scripts.
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### Recommendations
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Users are encouraged to use this model as Bash reference tool and should not execute commands without verification.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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def translate(prompt):
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model_name = "westenfelder/Llama-3.1-8B-Instruct-NL2SH"
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tokenizer = AutoTokenizer.from_pretrained(model_name, clean_up_tokenization_spaces=False)
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model = AutoModelForCausalLM.from_pretrained(model_name, device_map="cuda", torch_dtype=torch.bfloat16)
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messages = [
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{"role": "system", "content": "Your task is to translate a natural language instruction to a Bash command. You will receive an instruction in English and output a Bash command that can be run in a Linux terminal."},
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{"role": "user", "content": f"{prompt}"},
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]
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tokens = tokenizer.apply_chat_template(
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messages,
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add_generation_prompt=True,
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tokenize=True,
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return_tensors="pt"
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).to(model.device)
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attention_mask = torch.ones_like(tokens)
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terminators = [
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tokenizer.eos_token_id,
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tokenizer.convert_tokens_to_ids("<|eot_id|>")
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]
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outputs = model.generate(
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tokens,
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attention_mask=attention_mask,
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max_new_tokens=100,
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eos_token_id=terminators,
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pad_token_id=tokenizer.eos_token_id,
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do_sample=False,
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temperature=None,
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top_p=None,
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top_k=None,
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)
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response = outputs[0][tokens.shape[-1]:]
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return tokenizer.decode(response, skip_special_tokens=True)
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nl = "List files in the /workspace directory that were accessed over an hour ago."
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sh = translate(nl)
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print(sh)
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```
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## Training Details
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### Training Data
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This model was trained on the [NL2SH-ALFA](https://huggingface.co/datasets/westenfelder/NL2SH-ALFA) dataset.
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### Training Procedure
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Please refer to section 4.1 and 4.3.4 of the [paper](https://arxiv.org/abs/2502.06858) for information about data pre-processing, training hyper-parameters and hardware.
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## Evaluation
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This model was evaluated on the [NL2SH-ALFA](https://huggingface.co/datasets/westenfelder/NL2SH-ALFA) test set using the [InterCode-ALFA](https://github.com/westenfelder/InterCode-ALFA) benchmark.
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### Results
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This model achieved an accuracy of **0.40** on the InterCode-ALFA benchmark.
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## Environmental Impact
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Experiments were conducted using a private infrastructure, which has a approximate carbon efficiency of 0.432 kgCO2eq/kWh. A cumulative of 12 hours of computation was performed on hardware of type RTX A6000 (TDP of 300W). Total emissions are estimated to be 1.56 kgCO2eq of which 0 percents were directly offset. Estimations were conducted using the [Machine Learning Emissions Calculator](https://mlco2.github.io/impact#compute).
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## Citation
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**BibTeX:**
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```
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@misc{westenfelder2025llmsupportednaturallanguagebash,
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title={LLM-Supported Natural Language to Bash Translation},
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author={Finnian Westenfelder and Erik Hemberg and Miguel Tulla and Stephen Moskal and Una-May O'Reilly and Silviu Chiricescu},
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year={2025},
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eprint={2502.06858},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2502.06858},
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}
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```
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## Model Card Authors
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Finn Westenfelder
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## Model Card Contact
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Please email finnw@mit.edu or make a pull request.
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config.json
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"_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
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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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"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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"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": 128004,
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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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"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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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.46.3",
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"unsloth_version": "2024.11.10",
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"use_cache": true,
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"vocab_size": 128256
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}
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.46.3"
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"model.layers.6.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
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"model.layers.7.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
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"model.layers.7.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
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||||
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
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||||
"model.layers.8.input_layernorm.weight": "model-00001-of-00004.safetensors",
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||||
"model.layers.8.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
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"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
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||||
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"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
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||||
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||||
"model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
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||||
"model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
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||||
"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
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||||
"model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
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||||
"model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
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|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
17
special_tokens_map.json
Normal file
17
special_tokens_map.json
Normal file
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"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": "<|finetune_right_pad_id|>"
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
2064
tokenizer_config.json
Normal file
2064
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user