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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+SELM-Llama-3-8B-Instruct-iter-3 - GGUF
+- Model creator: https://huggingface.co/ZhangShenao/
+- Original model: https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-3/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q2_K.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q2_K.gguf) | Q2_K | 2.96GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.IQ3_XS.gguf) | IQ3_XS | 3.28GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.IQ3_S.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.IQ3_S.gguf) | IQ3_S | 3.43GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q3_K_S.gguf) | Q3_K_S | 3.41GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.IQ3_M.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.IQ3_M.gguf) | IQ3_M | 3.52GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q3_K.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q3_K.gguf) | Q3_K | 3.74GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q3_K_M.gguf) | Q3_K_M | 3.74GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q3_K_L.gguf) | Q3_K_L | 4.03GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.IQ4_XS.gguf) | IQ4_XS | 4.18GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q4_0.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q4_0.gguf) | Q4_0 | 4.34GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.IQ4_NL.gguf) | IQ4_NL | 4.38GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q4_K_S.gguf) | Q4_K_S | 4.37GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q4_K.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q4_K.gguf) | Q4_K | 4.58GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q4_K_M.gguf) | Q4_K_M | 4.58GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q4_1.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q4_1.gguf) | Q4_1 | 4.78GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q5_0.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q5_0.gguf) | Q5_0 | 5.21GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q5_K_S.gguf) | Q5_K_S | 5.21GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q5_K.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q5_K.gguf) | Q5_K | 5.34GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q5_K_M.gguf) | Q5_K_M | 5.34GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q5_1.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q5_1.gguf) | Q5_1 | 5.65GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q6_K.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q6_K.gguf) | Q6_K | 6.14GB |
+| [SELM-Llama-3-8B-Instruct-iter-3.Q8_0.gguf](https://huggingface.co/RichardErkhov/ZhangShenao_-_SELM-Llama-3-8B-Instruct-iter-3-gguf/blob/main/SELM-Llama-3-8B-Instruct-iter-3.Q8_0.gguf) | Q8_0 | 7.95GB |
+
+
+
+
+Original model description:
+---
+license: mit
+base_model: ZhangShenao/SELM-Llama-3-8B-Instruct-iter-2
+tags:
+- alignment-handbook
+- dpo
+- trl
+- selm
+datasets:
+- HuggingFaceH4/ultrafeedback_binarized
+model-index:
+- name: SELM-Llama-3-8B-Instruct-iter-3
+  results: []
+---
+
+
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+
+[Self-Exploring Language Models: Active Preference Elicitation for Online Alignment](https://arxiv.org/abs/2405.19332).
+
+
+
+# SELM-Llama-3-8B-Instruct-iter-3
+
+
+
+This model is a fine-tuned version of [ZhangShenao/SELM-Llama-3-8B-Instruct-iter-2](https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-2) using synthetic data based on on the HuggingFaceH4/ultrafeedback_binarized dataset.
+
+
+
+## Model description
+
+
+
+- Model type: A 8B parameter Llama3-instruct-based Self-Exploring Language Models (SELM).
+- License: MIT
+
+
+
+## Results
+
+
+
+|                                        | AlpacaEval 2.0 (LC WR) | MT-Bench (Average) |
+|----------------------------------------|------------------------|--------------------|
+| [SELM-Llama-3-8B-Instruct-iter-3](https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-3)  |    &emsp; &emsp; &emsp;&emsp;           33.47          |   &emsp; &emsp; &emsp;         8.29       |
+| [SELM-Llama-3-8B-Instruct-iter-2](https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-2) |    &emsp; &emsp; &emsp;&emsp;         35.65         |  &emsp; &emsp; &emsp;         8.09       |
+| [SELM-Llama-3-8B-Instruct-iter-1](https://huggingface.co/ZhangShenao/SELM-Llama-3-8B-Instruct-iter-1) |    &emsp; &emsp; &emsp;&emsp;         32.02         |  &emsp; &emsp; &emsp;         7.92       |
+| [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)  |    &emsp; &emsp; &emsp;&emsp;         24.31         |  &emsp; &emsp; &emsp;         7.93       |
+
+Our model also ranks highly on [WildBench](https://huggingface.co/spaces/allenai/WildBench)! 🔥
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- alpha: 0.0001
+- beta: 0.01
+- train_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- num_epochs: 1
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.14.6
+- Tokenizers 0.19.1
+
+