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README.md
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---
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library_name: peft
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base_model: mistralai/Mistral-7B-Instruct-v0.2
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---
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# Medical-Mixtral-7B-v2k
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## Description
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Fine-tuned Mixtral model for answering medical assistance questions. This model is a novel version of mistralai/
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## Intended Use
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This model is intended for providing assistance and answering questions related to medical inquiries. It is suitable for use in chatbot applications where users seek medical advice, information, or assistance.
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## Installation
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pip install -qU transformers==4.36.2 datasets python-dotenv peft bitsandbytes accelerate
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## Example Usage
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```python
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## Ethical Considerations
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Users should be informed that the model's responses are generated based on patterns in the training data and may not always be accurate or suitable for medical decision-making.
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The model should not be used as a replacement for professional medical advice or diagnosis.
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Sensitive patient data should not be shared with the model, and user privacy should be protected.
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---
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library_name: peft
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base_model: mistralai/Mistral-7B-Instruct-v0.2
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license: apache-2.0
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datasets:
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- ruslanmv/ai-medical-chatbot
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language:
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- en
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# Medical-Mixtral-7B-v2k
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[![](future.jpg)](https://ruslanmv.com/)
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## Description
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Fine-tuned Mixtral model for answering medical assistance questions. This model is a novel version of mistralai/Mistral-7B-Instruct-v0.2, adapted to a subset of 2.0k records from the AI Medical Chatbot dataset, which contains 250k records (https://huggingface.co/datasets/ruslanmv/ai-medical-chatbot). The purpose of this model is to provide a ready chatbot to answer questions related to medical assistance.
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## Intended Use
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This model is intended for providing assistance and answering questions related to medical inquiries. It is suitable for use in chatbot applications where users seek medical advice, information, or assistance.
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## Installation
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```
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pip install -qU transformers==4.36.2 datasets python-dotenv peft bitsandbytes accelerate
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```
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## Example Usage
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```python
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## Ethical Considerations
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Users should be informed that the model's responses are generated based on patterns in the training data and may not always be accurate or suitable for medical decision-making.
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The model should not be used as a replacement for professional medical advice or diagnosis.
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Sensitive patient data should not be shared with the model, and user privacy should be protected.
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