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Improve language tag

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Hi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.

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  1. README.md +83 -69
README.md CHANGED
@@ -1,70 +1,84 @@
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- ---
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- base_model: Qwen/Qwen2.5-1.5B-Instruct
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- library_name: transformers
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- model_name: Qwen2.5-1.5B-Instruct-FT-DPO
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- tags:
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- - generated_from_trainer
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- - smol-course
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- - module_1
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- - trl
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- - dpo
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- licence: license
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- ---
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-
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- # Model Card for Qwen2.5-1.5B-Instruct-FT-DPO
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-
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- This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct).
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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="sdpkjc/Qwen2.5-1.5B-Instruct-FT-DPO", 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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- 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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- - TRL: 0.12.1
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- - Transformers: 4.46.0
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- - Pytorch: 2.5.1
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- - Datasets: 3.1.0
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- - Tokenizers: 0.20.3
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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 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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+ ---
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+ base_model: Qwen/Qwen2.5-1.5B-Instruct
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+ library_name: transformers
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+ model_name: Qwen2.5-1.5B-Instruct-FT-DPO
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+ tags:
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+ - generated_from_trainer
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+ - smol-course
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+ - module_1
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+ - trl
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+ - dpo
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+ licence: license
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+ language:
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+ - zho
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+ - eng
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+ - fra
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+ - spa
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+ - por
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+ - deu
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+ - ita
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+ - rus
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+ - jpn
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+ - kor
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+ - vie
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+ - tha
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+ - ara
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+ ---
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+
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+ # Model Card for Qwen2.5-1.5B-Instruct-FT-DPO
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+
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+ This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct).
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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="sdpkjc/Qwen2.5-1.5B-Instruct-FT-DPO", 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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+ 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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+ - TRL: 0.12.1
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+ - Transformers: 4.46.0
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+ - Pytorch: 2.5.1
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+ - Datasets: 3.1.0
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+ - Tokenizers: 0.20.3
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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 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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  ```