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Model: lldois/SmolLM2-135M-Reasoning-Beta001-Champion Source: Original Platform
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README.md
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---
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library_name: transformers
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model_name: exp133_dpo_exp035_beta001
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tags:
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- generated_from_trainer
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- dpo
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- trl
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licence: license
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---
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# Model Card for exp133_dpo_exp035_beta001
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This model is a fine-tuned version of [None](https://huggingface.co/None).
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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/lldois-ll/trlm-plus-copilot/runs/iwpjyp0a)
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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: 0.27.1
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- Transformers: 4.57.6
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- Pytorch: 2.8.0+metax3.3.0.2
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- Datasets: 4.5.0
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- Tokenizers: 0.22.1
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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 Gallou{\'e}dec},
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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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added_tokens.json
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{
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"</think>": 49153,
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"<think>": 49152
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}
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chat_template.jinja
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{% for message in messages %}{{'<|im_start|>' + message['role'] + '
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' + message['content'] + '<|im_end|>' + '
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'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
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' }}{% endif %}
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config.json
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config.json
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{
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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": 1,
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"dtype": "bfloat16",
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"eos_token_id": 2,
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"head_dim": 64,
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"hidden_act": "silu",
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"hidden_size": 576,
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"initializer_range": 0.041666666666666664,
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"intermediate_size": 1536,
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"is_llama_config": true,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 9,
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"num_hidden_layers": 30,
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"num_key_value_heads": 3,
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"pad_token_id": 2,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_interleaved": false,
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"rope_scaling": null,
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"rope_theta": 100000,
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"tie_word_embeddings": true,
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"fp16": "float16",
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}
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generation_config.json
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merges.txt
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model.safetensors
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special_tokens_map.json
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3
training_args.bin
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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size 6993
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vocab.json
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vocab.json
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