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--- |
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license: mit |
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language: |
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- en |
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base_model: |
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- meta-llama/Meta-Llama-3-8B-Instruct |
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library_name: transformers |
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--- |
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# LLaMA 3 8B - ChatDoctor Model |
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## Model Description |
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This is a fine-tuned version of the **LLaMA 3 8B** model. The model is fine-tuned on medical conversations to assist healthcare professionals and users in understanding medical-related queries. It’s designed for natural language understanding and generation, focusing on medical advice and diagnostics. |
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- **Base Model:** LLaMA 3 8B |
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- **Fine-Tuned On:** Medical QA dataset (or specify other datasets) |
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- **Model Type:** Causal Language Model (CLM) |
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## Intended Use |
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This model is intended for generating conversational responses related to medical diagnostics, symptom analysis, or any medical-related inquiry. It is designed to assist in providing informative and preliminary medical guidance based on the fine-tuned datasets. |
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### Use Cases: |
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- Medical chatbots. |
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- Healthcare consultation apps. |
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- Symptom analysis. |
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### Limitations: |
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- **Not a replacement for professional medical advice**: The model is trained on limited datasets and should not be used as a standalone diagnostic tool. |
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- **Language Bias**: It may show biases based on the data it was trained on. |
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## How to Use |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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# Load the fine-tuned model and tokenizer |
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model = AutoModelForCausalLM.from_pretrained("abhiyanta/llama-chatdoctor") |
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tokenizer = AutoTokenizer.from_pretrained("abhiyanta/llama-chatdoctor") |
