RichardErkhov/alpindale_-_pygmalion-instruct-gguf

Quantization made by Richard Erkhov.

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pygmalion-instruct - GGUF

• Model creator: https://huggingface.co/alpindale/
• Original model: https://huggingface.co/alpindale/pygmalion-instruct/

Name	Quant method	Size
pygmalion-instruct.Q2_K.gguf	Q2_K	2.36GB
pygmalion-instruct.IQ3_XS.gguf	IQ3_XS	2.6GB
pygmalion-instruct.IQ3_S.gguf	IQ3_S	2.75GB
pygmalion-instruct.Q3_K_S.gguf	Q3_K_S	2.75GB
pygmalion-instruct.IQ3_M.gguf	IQ3_M	2.9GB
pygmalion-instruct.Q3_K.gguf	Q3_K	3.07GB
pygmalion-instruct.Q3_K_M.gguf	Q3_K_M	3.07GB
pygmalion-instruct.Q3_K_L.gguf	Q3_K_L	3.35GB
pygmalion-instruct.IQ4_XS.gguf	IQ4_XS	3.4GB
pygmalion-instruct.Q4_0.gguf	Q4_0	3.56GB
pygmalion-instruct.IQ4_NL.gguf	IQ4_NL	3.58GB
pygmalion-instruct.Q4_K_S.gguf	Q4_K_S	3.59GB
pygmalion-instruct.Q4_K.gguf	Q4_K	3.8GB
pygmalion-instruct.Q4_K_M.gguf	Q4_K_M	3.8GB
pygmalion-instruct.Q4_1.gguf	Q4_1	3.95GB
pygmalion-instruct.Q5_0.gguf	Q5_0	4.33GB
pygmalion-instruct.Q5_K_S.gguf	Q5_K_S	4.33GB
pygmalion-instruct.Q5_K.gguf	Q5_K	4.45GB
pygmalion-instruct.Q5_K_M.gguf	Q5_K_M	4.45GB
pygmalion-instruct.Q5_1.gguf	Q5_1	4.72GB
pygmalion-instruct.Q6_K.gguf	Q6_K	5.15GB

Original model description:

license: mit

Model Details

Experimental model. Trained with the Pygmalion and the WizardLM datasets.

The purpose of this model is to enable complex Instruct prompting but with the RP capabilties of Pygmalion.

Prompting format

instruction:
output:

• Repository: [More Information Needed]
• Paper [optional]: [More Information Needed]
• Demo [optional]: [More Information Needed]

Uses

The intended use-case is Role-Playing with Instruct prompts. Guiding the bot towards a certain conversation style should be easier this way. Subject to experimentation.

Out-of-Scope Use

• Assistant Bot [subject to providing incorrect instructions]
• Complex multi-character chat

Risks

The model can generate potentially harmful or NSFW outputs. Please use with caution.

Citation

WizardLM:

@misc{xu2023wizardlm,
      title={WizardLM: Empowering Large Language Models to Follow Complex Instructions}, 
      author={Can Xu and Qingfeng Sun and Kai Zheng and Xiubo Geng and Pu Zhao and Jiazhan Feng and Chongyang Tao and Daxin Jiang},
      year={2023},
      eprint={2304.12244},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}