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StableLM2-1.6B-Email-DPO-Hybrid

Text Generation
PEFT
Safetensors
Transformers
stablelm
dpo
lora
trl
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  1. README.md +73 -0
  2. chat_template.jinja +15 -0
  3. config.json +30 -0
  4. generation_config.json +8 -0
  5. merges.txt +0 -0
  6. model.safetensors +3 -0
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  15. peft/training_info.yaml +37 -0
  16. peft/vocab.json +0 -0
  17. special_tokens_map.json +65 -0
  18. tokenizer.json +0 -0
  19. tokenizer_config.json +312 -0
  20. vocab.json +0 -0
README.md ADDED
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+ ---
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+ base_model: stabilityai/stablelm-2-zephyr-1_6b
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+ library_name: peft
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+ model_name: dpo_stablelm_20250721_052154
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+ tags:
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+ - base_model:adapter:stabilityai/stablelm-2-zephyr-1_6b
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+ - dpo
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+ - lora
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+ - transformers
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+ - trl
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+ licence: license
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # Model Card for dpo_stablelm_20250721_052154
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+
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+ This model is a fine-tuned version of [stabilityai/stablelm-2-zephyr-1_6b](https://huggingface.co/stabilityai/stablelm-2-zephyr-1_6b).
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+ It has been trained using [TRL](https://github.com/huggingface/trl).
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+
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+ ## Quick start
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+
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+ ```python
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+ from transformers import pipeline
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+
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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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+
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+ ## Training procedure
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+
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+
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+
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+
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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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+
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+ ### Framework versions
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+
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+ - PEFT 0.16.0
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+ - TRL: 0.19.1
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+ - Transformers: 4.53.2
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+ - Pytorch: 2.6.0
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+ - Datasets: 4.0.0
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+ - Tokenizers: 0.21.2
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+
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+ ## Citations
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+
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+ Cite DPO as:
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+
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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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+
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+ Cite TRL as:
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+
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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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+ {% for message in messages %}
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+ {% if message['role'] == 'user' %}
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+ {{ '<|user|>
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+ ' + message['content'] + eos_token }}
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+ {% elif message['role'] == 'system' %}
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+ {% elif message['role'] == 'assistant' %}
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+ {{ '<|assistant|>
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+ {% endfor %}
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