Model save

README.md

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+---
+library_name: transformers
+model_name: trained_ppo_model
+tags:
+- generated_from_trainer
+licence: license
+---
+
+# Model Card for trained_ppo_model
+
+This model is a fine-tuned version of [None](https://huggingface.co/None).
+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="joaoluislins/trained_ppo_model", 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/stevens_ml/huggingface/runs/o7ck84zq) 
+
+
+This model was trained with PPO, a method introduced in [Fine-Tuning Language Models from Human Preferences](https://huggingface.co/papers/1909.08593).
+
+### Framework versions
+
+- TRL: 0.13.0
+- Transformers: 4.46.2
+- Pytorch: 2.5.1
+- Datasets: 3.2.0
+- Tokenizers: 0.20.3
+
+## Citations
+
+Cite PPO as:
+
+```bibtex
+@article{mziegler2019fine-tuning,
+    title        = {{Fine-Tuning Language Models from Human Preferences}},
+    author       = {Daniel M. Ziegler and Nisan Stiennon and Jeffrey Wu and Tom B. Brown and Alec Radford and Dario Amodei and Paul F. Christiano and Geoffrey Irving},
+    year         = 2019,
+    eprint       = {arXiv:1909.08593}
+}
+```
+
+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 Gallouédec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```