RichardErkhov
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README.md
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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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[Request more models](https://github.com/RichardErkhov/quant_request)
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prometheus-2-llama-3-8b - GGUF
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- Model creator: https://huggingface.co/chargoddard/
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- Original model: https://huggingface.co/chargoddard/prometheus-2-llama-3-8b/
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| Name | Quant method | Size |
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| ---- | ---- | ---- |
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| [prometheus-2-llama-3-8b.Q2_K.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q2_K.gguf) | Q2_K | 2.96GB |
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| [prometheus-2-llama-3-8b.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.IQ3_XS.gguf) | IQ3_XS | 3.28GB |
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| [prometheus-2-llama-3-8b.IQ3_S.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.IQ3_S.gguf) | IQ3_S | 3.43GB |
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| [prometheus-2-llama-3-8b.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q3_K_S.gguf) | Q3_K_S | 3.41GB |
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| [prometheus-2-llama-3-8b.IQ3_M.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.IQ3_M.gguf) | IQ3_M | 3.52GB |
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| [prometheus-2-llama-3-8b.Q3_K.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q3_K.gguf) | Q3_K | 3.74GB |
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| [prometheus-2-llama-3-8b.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q3_K_M.gguf) | Q3_K_M | 3.74GB |
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| [prometheus-2-llama-3-8b.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q3_K_L.gguf) | Q3_K_L | 4.03GB |
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| [prometheus-2-llama-3-8b.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.IQ4_XS.gguf) | IQ4_XS | 4.18GB |
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| [prometheus-2-llama-3-8b.Q4_0.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q4_0.gguf) | Q4_0 | 4.34GB |
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| [prometheus-2-llama-3-8b.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.IQ4_NL.gguf) | IQ4_NL | 4.38GB |
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| [prometheus-2-llama-3-8b.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q4_K_S.gguf) | Q4_K_S | 4.37GB |
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| [prometheus-2-llama-3-8b.Q4_K.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q4_K.gguf) | Q4_K | 4.58GB |
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| [prometheus-2-llama-3-8b.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q4_K_M.gguf) | Q4_K_M | 4.58GB |
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| [prometheus-2-llama-3-8b.Q4_1.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q4_1.gguf) | Q4_1 | 4.78GB |
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| [prometheus-2-llama-3-8b.Q5_0.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q5_0.gguf) | Q5_0 | 5.21GB |
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| [prometheus-2-llama-3-8b.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q5_K_S.gguf) | Q5_K_S | 5.21GB |
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| [prometheus-2-llama-3-8b.Q5_K.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q5_K.gguf) | Q5_K | 5.34GB |
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| [prometheus-2-llama-3-8b.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q5_K_M.gguf) | Q5_K_M | 5.34GB |
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| [prometheus-2-llama-3-8b.Q5_1.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q5_1.gguf) | Q5_1 | 5.65GB |
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| [prometheus-2-llama-3-8b.Q6_K.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q6_K.gguf) | Q6_K | 6.14GB |
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| [prometheus-2-llama-3-8b.Q8_0.gguf](https://huggingface.co/RichardErkhov/chargoddard_-_prometheus-2-llama-3-8b-gguf/blob/main/prometheus-2-llama-3-8b.Q8_0.gguf) | Q8_0 | 7.95GB |
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Original model description:
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---
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base_model:
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- chargoddard/prometheus-llama-3-8b-preference
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- chargoddard/prometheus-llama-3-8b-absolute
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library_name: transformers
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tags:
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- mergekit
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- merge
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license: apache-2.0
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datasets:
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- prometheus-eval/Preference-Collection
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- prometheus-eval/Feedback-Collection
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language:
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- en
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---
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# prometheus-2-llama-3-8b
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Replication of [prometheus-7b-v2.0](https://huggingface.co/prometheus-eval/prometheus-7b-v2.0) using [Llama 3 8B Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base model.
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As in their paper, two different models were trained on their preference and feedback datasets then linearly merged at equal weight.
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Training hyperparameters:
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* 1 epoch
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* Learning rate 1e-5
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* Effective batch size 128
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* Cosine annealing
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* ~5% warmup
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Uses Llama 3 Instruct prompt format and the same prompts as prometheus-7b-v2.0. See that readme for info.
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# Citations
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```bibtex
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@misc{kim2023prometheus,
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title={Prometheus: Inducing Fine-grained Evaluation Capability in Language Models},
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author={Seungone Kim and Jamin Shin and Yejin Cho and Joel Jang and Shayne Longpre and Hwaran Lee and Sangdoo Yun and Seongjin Shin and Sungdong Kim and James Thorne and Minjoon Seo},
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year={2023},
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eprint={2310.08491},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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```bibtex
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@misc{kim2024prometheus,
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title={Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models},
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author={Seungone Kim and Juyoung Suk and Shayne Longpre and Bill Yuchen Lin and Jamin Shin and Sean Welleck and Graham Neubig and Moontae Lee and Kyungjae Lee and Minjoon Seo},
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year={2024},
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eprint={2405.01535},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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