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RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf

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+ Quantization made by Richard Erkhov.
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+ [Github](https://github.com/RichardErkhov)
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+ [Discord](https://discord.gg/pvy7H8DZMG)
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+
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+ [Request more models](https://github.com/RichardErkhov/quant_request)
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+
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+ self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2 - GGUF
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+ - Model creator: https://huggingface.co/RyanYr/
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+ - Original model: https://huggingface.co/RyanYr/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2/
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+
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+
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+ | Name | Quant method | Size |
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+ | ---- | ---- | ---- |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q2_K.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q2_K.gguf) | Q2_K | 2.97GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q3_K_S.gguf) | Q3_K_S | 3.41GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q3_K.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q3_K.gguf) | Q3_K | 3.74GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q3_K_M.gguf) | Q3_K_M | 3.74GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q3_K_L.gguf) | Q3_K_L | 4.03GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.IQ4_XS.gguf) | IQ4_XS | 4.17GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_0.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_0.gguf) | Q4_0 | 4.34GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.IQ4_NL.gguf) | IQ4_NL | 4.38GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_K_S.gguf) | Q4_K_S | 4.36GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_K.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_K.gguf) | Q4_K | 4.57GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_K_M.gguf) | Q4_K_M | 4.57GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_1.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q4_1.gguf) | Q4_1 | 4.77GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_0.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_0.gguf) | Q5_0 | 2.65GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_K_S.gguf) | Q5_K_S | 4.72GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_K.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_K.gguf) | Q5_K | 5.33GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_K_M.gguf) | Q5_K_M | 5.33GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_1.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q5_1.gguf) | Q5_1 | 5.65GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q6_K.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q6_K.gguf) | Q6_K | 6.14GB |
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+ | [self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q8_0.gguf](https://huggingface.co/RichardErkhov/RyanYr_-_self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2-gguf/blob/main/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2.Q8_0.gguf) | Q8_0 | 7.94GB |
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+
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+
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+
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+ Original model description:
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+ ---
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+ base_model: RyanYr/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter1
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+ library_name: transformers
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+ model_name: self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2
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+ tags:
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+ - generated_from_trainer
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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 self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2
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+
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+ This model is a fine-tuned version of [RyanYr/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter1](https://huggingface.co/RyanYr/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter1).
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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="RyanYr/self-correct_Ministral-8B-Instruct-2410_metaMathQA_dpo_iter2", 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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+ [<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/yyr/huggingface/runs/86tsr409)
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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: 0.12.0.dev0
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+ - Transformers: 4.45.2
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+ - Pytorch: 2.4.0
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+ - Datasets: 3.0.2
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+ - Tokenizers: 0.20.1
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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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+