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  - llama
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  - self-instruct
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  - distillation
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  - llama
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  - self-instruct
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  - distillation
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+ ---
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+ # Model Card: Nous-Hermes-13b
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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 developed and fine-tuned by Teknium, in collaboration with Nous Research, Redmond AI, 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from diverse sources such as GPTeacher, the general, roleplay v1&2, code instruct datasets, Nous Instruct & PDACTL (unpublished), CodeAlpaca, Evol_Instruct Uncensored, GPT4-LLM, and Unnatural Instructions.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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+ ## Collaborators
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+ The model fine-tuning and the datasets were a collaboration of efforts and resources between Teknium, Karan4D, Nous Research, Huemin Art, and Redmond AI.
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+ Huge shoutout and acknowledgement is deserved for all the dataset creators who generously share their datasets openly.
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+ Special mention goes to @winglian, @erhartford, and @main_horse for assisting in some of the training issues.
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+ Among the contributors of datasets, GPTeacher was made available by Teknium, Wizard LM by nlpxucan, and the Nous Research Instruct Dataset was provided by Karan4D and HueminArt.
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+ The GPT4-LLM and Unnatural Instructions were provided by Microsoft, Airoboros dataset by jondurbin, Camel-AI datasets are from Camel-AI, and CodeAlpaca dataset by Sahil 2801.
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+ If anyone was left out, please open a thread in the community tab.
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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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+ ## Future Plans
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+ The model is currently being uploaded in FP16 format, and there are plans to convert the model to GGML and GPTQ 4bit quantizations. The team is also working on a full benchmark, similar to what was done for GPT4-x-Vicuna. We will try to get in discussions to get the model included in the GPT4All.
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+ ## Benchmark Results
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+ Benchmark results are coming soon.
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+ ## Model Usage
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+ The model is available for download on Hugging Face. It is suitable for a wide range of language tasks, from generating creative text to understanding and following complex instructions.
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+ Compute provided by our project sponsor Redmond AI, thank you!!