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README.md
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---
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license: other
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language:
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- en
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pipeline_tag: text-generation
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inference: false
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tags:
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- transformers
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- gguf
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- imatrix
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- Nous-Hermes-13b
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---
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Quantizations of https://huggingface.co/NousResearch/Nous-Hermes-13b
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### Inference Clients/UIs
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* [llama.cpp](https://github.com/ggerganov/llama.cpp)
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* [KoboldCPP](https://github.com/LostRuins/koboldcpp)
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* [ollama](https://github.com/ollama/ollama)
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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* [GPT4All](https://github.com/nomic-ai/gpt4all)
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* [jan](https://github.com/janhq/jan)
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---
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# From original readme
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## Model Description
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Nous-Hermes-13b is a state-of-the-art language model fine-tuned on over 300,000 instructions. This model was fine-tuned by Nous Research, with Teknium and Karan4D leading the fine tuning process and dataset curation, Redmond AI sponsoring the compute, and several other contributors. The result is an enhanced Llama 13b model that rivals GPT-3.5-turbo in performance across a variety of tasks.
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This model stands out for its long responses, low hallucination rate, and absence of OpenAI censorship mechanisms. The fine-tuning process was performed with a 2000 sequence length on an 8x a100 80GB DGX machine for over 50 hours.
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## Model Training
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The model was trained almost entirely on synthetic GPT-4 outputs. This includes data from diverse sources such as GPTeacher, the general, roleplay v1&2, code instruct datasets, Nous Instruct & PDACTL (unpublished), CodeAlpaca, Evol_Instruct Uncensored, GPT4-LLM, and Unnatural Instructions.
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Additional data inputs came from Camel-AI's Biology/Physics/Chemistry and Math Datasets, Airoboros' GPT-4 Dataset, and more from CodeAlpaca. The total volume of data encompassed over 300,000 instructions.
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## Prompt Format
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The model follows the Alpaca prompt format:
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```
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### Instruction:
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### Response:
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```
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or
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```
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### Instruction:
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### Input:
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### Response:
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```
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