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Model: Thrillcrazyer/Qwen-7B_TAC_RLOO
Source: Original Platform

README.md

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+---
+base_model: Qwen/Qwen2.5-7B-Instruct
+datasets: DeepMath-103k
+library_name: transformers
+model_name: Qwen-7B_TAC_RLOO
+tags:
+- generated_from_trainer
+- rloo
+- trl
+licence: license
+---
+
+# Model Card for Qwen-7B_TAC_RLOO
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the [DeepMath-103k](https://huggingface.co/datasets/DeepMath-103k) dataset.
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+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?"
+generator = pipeline("text-generation", model="Thrillcrazyer/Qwen-7B_TAC_RLOO", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<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/pthpark1/TAC/runs/arcccs2h) 
+
+
+This model was trained with RLOO, a method introduced in [Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs](https://huggingface.co/papers/2402.14740).
+
+### Framework versions
+
+- TRL: 0.26.2
+- Transformers: 4.57.3
+- Pytorch: 2.8.0
+- Datasets: 4.4.2
+- Tokenizers: 0.22.1
+
+## Citations
+
+Cite RLOO as:
+
+```bibtex
+@inproceedings{ahmadian2024back,
+    title        = {{Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs}},
+    author       = {Arash Ahmadian and Chris Cremer and Matthias Gall{'{e}} and Marzieh Fadaee and Julia Kreutzer and Olivier Pietquin and Ahmet {"{U}}st{"{u}}n and Sara Hooker},
+    year         = 2024,
+    booktitle    = {Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), {ACL} 2024, Bangkok, Thailand, August 11-16, 2024},
+    pages        = {12248--12267},
+    publisher    = {Association for Computational Linguistics},
+    editor       = {Lun{-}Wei Ku and Andre Martins and Vivek Srikumar},
+}
+```
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	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},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```