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‼️ This model is still in a beta state. It will be retrained at a future data and updated, during which its prompting format may change. If you need to depend on it in its current state, please create your own fork and provide attribution to this original repository. ‼️
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Llama Functions is a further fine-tuned version of [Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), using
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The function calling dataset is mixed with Guanaco in order to maintain accuracy and helpfulness when calling a function is not the appropriate response. Guidelines for use, more detailed information regarding limitations, and eval stats of 7B, 13B, and 70B models.
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There is no existing evaluation benchmark to measure the accuracy of function calls, which makes it hard during training to identify when we've maximized the balance of function calling accuracy and chat model performance. I'm working on a custom HF eval for this purpose, but until then I have chosen to mix the two datasets in equal parts to get a proxy of performance for both tasks in the eval & test stats during fine-tuning. The current checkpoint is at 1000 steps, when eval & test loss reached their lowest point.
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- **Developed by:** Marc Love
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- **License:** [
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- **Finetuned from:** [Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
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### Model Sources [optional]
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## Uses
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Please note
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## Bias, Risks, and Limitations
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‼️ This model is still in a beta state. It will be retrained at a future data and updated, during which its prompting format may change. If you need to depend on it in its current state, please create your own fork and provide attribution to this original repository. ‼️
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Llama Functions is a further fine-tuned version of [Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), using a 50/50 mix of:
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1. Synthetic OpenAPI function calls with their corresponding natural language invocation, and
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2. Chat completions from the [Guanaco subset of the OASST1 dataset](https://huggingface.co/datasets/timdettmers/openassistant-guanaco).
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13B & 70B versions are coming soon.
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The function calling dataset is mixed with Guanaco in order to maintain accuracy and helpfulness when calling a function is not the appropriate response. Guidelines for use, more detailed information regarding limitations, and eval stats of 7B, 13B, and 70B models.
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There is no existing evaluation benchmark to measure the accuracy of function calls, which makes it hard during training to identify when we've maximized the balance of function calling accuracy and chat model performance. I'm working on a custom HF eval for this purpose, but until then I have chosen to mix the two datasets in equal parts to get a proxy of performance for both tasks in the eval & test stats during fine-tuning. The current checkpoint is at 1000 steps, when eval & test loss reached their lowest point.
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- **Developed by:** Marc Love
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- **License:** [Llama 2 Community License](https://ai.meta.com/llama/license/)
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- **Finetuned from:** [Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)
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### Model Sources [optional]
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## Uses
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**Please note:** The synthetic data portion of the dataset was generated using OpenAI models. This model is released under the Llama 2 Community License, per the Llama 2 Community License Agreement. Since I fine-tuned them model on OpenAI generated data that I generated, this model is released for research purposes only. I have licensed the associated `llama_functions` dataset under the [Creative Commons' Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license](https://creativecommons.org/licenses/by-sa/4.0/). Whether you may use that data to train your own models is your responsibility to determine.
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## Bias, Risks, and Limitations
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