Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +69 -0
- adapter_config.json +37 -0
- adapter_model.bin +3 -0
- config.json +44 -0
- generation_config.json +9 -0
- pytorch_model-00001-of-00002.bin +3 -0
- pytorch_model-00002-of-00002.bin +3 -0
- pytorch_model.bin.index.json +0 -0
- special_tokens_map.json +30 -0
- tokenizer.json +3 -0
- tokenizer_config.json +0 -0
.gitattributes
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README.md
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---
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base_model: unsloth/Mistral-Nemo-Base-2407-bnb-4bit
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datasets:
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- rinen0721/rica_dpo
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library_name: transformers
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model_name: workspace/dpo/model
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tags:
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- generated_from_trainer
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- unsloth
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licence: license
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---
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# Model Card for workspace/dpo/model
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This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407-bnb-4bit](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407-bnb-4bit) on the [['rinen0721/rica_dpo']](https://huggingface.co/datasets/['rinen0721/rica_dpo']) dataset.
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="None", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/rinen-exp/exp1/runs/ahoc1vyr)
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
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### Framework versions
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- TRL: 0.12.1
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- Transformers: 4.47.1
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- Pytorch: 2.5.1
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- Datasets: 3.1.0
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- Tokenizers: 0.21.0
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## Citations
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Cite DPO as:
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```bibtex
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@inproceedings{rafailov2023direct,
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title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}},
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author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn},
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year = 2023,
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booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023},
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url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html},
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editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine},
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}
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```
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "unsloth/Mistral-Nemo-Base-2407-bnb-4bit",
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"bias": "none",
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"q_proj",
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"k_proj",
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"up_proj",
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"o_proj",
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"v_proj",
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"down_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.bin
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size 456332938
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config.json
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{
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"_name_or_path": "unsloth/Mistral-Nemo-Base-2407-bnb-4bit",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"hidden_size": 5120,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_key_value_heads": 8,
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"quantization_config": {
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"_load_in_4bit": true,
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"_load_in_8bit": false,
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"bnb_4bit_compute_dtype": "bfloat16",
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"bnb_4bit_quant_storage": "uint8",
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"bnb_4bit_quant_type": "nf4",
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"bnb_4bit_use_double_quant": true,
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_skip_modules": null,
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"llm_int8_threshold": 6.0,
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"load_in_4bit": true,
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"load_in_8bit": false,
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"quant_method": "bitsandbytes"
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},
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"sliding_window": null,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.47.1",
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"unsloth_version": "2024.9",
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}
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generation_config.json
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}
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pytorch_model.bin.index.json
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special_tokens_map.json
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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tokenizer_config.json
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