Update README.md

README.md

@@ -14,22 +14,8 @@ licence: license
 This model is a fine-tuned version of [Shekswess/tiny-think-sft-math-stem-loss-nll-bf16-lr2e-5-e2-bs8](https://huggingface.co/Shekswess/tiny-think-sft-math-stem-loss-nll-bf16-lr2e-5-e2-bs8).
 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="Shekswess/tiny-think-dpo-math-stem-apo_zero-beta0_3-lr3e-6-e1-bs8", 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/bokicasheks-loka/tiny_think/runs/7aerg1ht) 
-
-
 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).
 
 ### Framework versions
@@ -38,32 +24,4 @@ This model was trained with DPO, a method introduced in [Direct Preference Optim
 - Transformers: 4.57.5
 - Pytorch: 2.9.0+cu128
 - Datasets: 4.5.0
-- Tokenizers: 0.22.2
-
-## Citations
-
-Cite DPO as:
-
-```bibtex
-@inproceedings{rafailov2023direct,
-    title        = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}},
-    author       = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn},
-    year         = 2023,
-    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},
-    url          = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html},
-    editor       = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine},
-}
-```
-
-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}}
-}
-```
+- Tokenizers: 0.22.2