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- ---
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- base_model: Qwen/Qwen2.5-32B-Instruct
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- library_name: transformers
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- model_name: Qwen2.5-32B-Instruct-20250119_201826
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- tags:
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- - generated_from_trainer
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- - trl
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- - sft
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- licence: license
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- ---
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- # Model Card for Qwen2.5-32B-Instruct-20250119_201826
 
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- This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct).
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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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-
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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="qfq/Qwen2.5-32B-Instruct-20250119_201826", 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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  [<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/hashimoto-group/o1/runs/xaantfal)
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-
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- This model was trained with SFT.
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-
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- ### Framework versions
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-
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  - TRL: 0.13.0
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  - Transformers: 4.48.0
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  - Pytorch: 2.3.1
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  - Datasets: 3.0.1
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  - Tokenizers: 0.21.0
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- ## Citations
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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 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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+ # Model Summary
 
 
 
 
 
 
 
 
 
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+ - **Repository:** [simplescaling/s1](https://github.com/simplescaling/s1)
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+ - **Paper:** TODO
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+ # Use
 
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+ This is the token-conditional control model for our paper. You can evaluate using the information [here](https://github.com/simplescaling/s1?tab=readme-ov-file#evaluation).
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+ # Training information
 
 
 
 
 
 
 
 
 
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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/hashimoto-group/o1/runs/xaantfal)
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  - TRL: 0.13.0
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  - Transformers: 4.48.0
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  - Pytorch: 2.3.1
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  - Datasets: 3.0.1
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  - Tokenizers: 0.21.0
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+ # Citation
 
 
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  ```bibtex
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+ TODO
 
 
 
 
 
 
 
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  ```