Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


zephyr-7b-sft-full-SPIN-iter0 - GGUF
- Model creator: https://huggingface.co/UCLA-AGI/
- Original model: https://huggingface.co/UCLA-AGI/zephyr-7b-sft-full-SPIN-iter0/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [zephyr-7b-sft-full-SPIN-iter0.Q2_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q2_K.gguf) | Q2_K | 2.53GB |
| [zephyr-7b-sft-full-SPIN-iter0.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.IQ3_XS.gguf) | IQ3_XS | 2.81GB |
| [zephyr-7b-sft-full-SPIN-iter0.IQ3_S.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.IQ3_S.gguf) | IQ3_S | 2.96GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q3_K_S.gguf) | Q3_K_S | 2.95GB |
| [zephyr-7b-sft-full-SPIN-iter0.IQ3_M.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.IQ3_M.gguf) | IQ3_M | 3.06GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q3_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q3_K.gguf) | Q3_K | 3.28GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q3_K_M.gguf) | Q3_K_M | 3.28GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q3_K_L.gguf) | Q3_K_L | 3.56GB |
| [zephyr-7b-sft-full-SPIN-iter0.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.IQ4_XS.gguf) | IQ4_XS | 3.67GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q4_0.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q4_0.gguf) | Q4_0 | 3.83GB |
| [zephyr-7b-sft-full-SPIN-iter0.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.IQ4_NL.gguf) | IQ4_NL | 3.87GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q4_K_S.gguf) | Q4_K_S | 3.86GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q4_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q4_K.gguf) | Q4_K | 4.07GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q4_K_M.gguf) | Q4_K_M | 4.07GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q4_1.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q4_1.gguf) | Q4_1 | 4.24GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q5_0.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q5_0.gguf) | Q5_0 | 4.65GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q5_K_S.gguf) | Q5_K_S | 4.65GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q5_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q5_K.gguf) | Q5_K | 4.78GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q5_K_M.gguf) | Q5_K_M | 4.78GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q5_1.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q5_1.gguf) | Q5_1 | 5.07GB |
| [zephyr-7b-sft-full-SPIN-iter0.Q6_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_zephyr-7b-sft-full-SPIN-iter0-gguf/blob/main/zephyr-7b-sft-full-SPIN-iter0.Q6_K.gguf) | Q6_K | 5.53GB |




Original model description:
---
license: mit
datasets:
- UCLA-AGI/SPIN_iter0
language:
- en
pipeline_tag: text-generation
---
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models (https://arxiv.org/abs/2401.01335)

# zephyr-7b-sft-full-spin-iter0

This model is a self-play fine-tuned model at iteration 0 from [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) using synthetic data based on on the [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k) dataset.

## Model Details

### Model Description

- Model type: A 7B parameter GPT-like model fine-tuned on synthetic datasets.
- Language(s) (NLP): Primarily English
- License: MIT
- Finetuned from model: alignment-handbook/zephyr-7b-sft-full (based on mistralai/Mistral-7B-v0.1)

### Training hyperparameters
The following hyperparameters were used during training:

- learning_rate: 5e-07
- train_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- optimizer: RMSProp 
- lr_scheduler_type: linear 
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0

## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_UCLA-AGI__test0)
| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 62.37   |
| ARC (25-shot)         | 63.65          |
| HellaSwag (10-shot)   | 84.44    |
| MMLU (5-shot)         | 61.01         |
| TruthfulQA (0-shot)   | 50.48   |
| Winogrande (5-shot)   | 77.98   |
| GSM8K (5-shot)        | 36.69        |
  
## Citation
```
@misc{chen2024selfplay,
      title={Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models}, 
      author={Zixiang Chen and Yihe Deng and Huizhuo Yuan and Kaixuan Ji and Quanquan Gu},
      year={2024},
      eprint={2401.01335},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
```