jeevanrushi07/medical_chatbot

finetuned model

Prompt

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Prompt

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Model description

Model Description This is a fine-tuned LLaMA-based causal language model using LoRA (Low-Rank Adaptation) for efficient domain-specific learning. The model generates text autoregressively, producing one token at a time based on the conversation history and user input.

It is particularly adapted to generate medical reports based on patient metadata (age, gender, symptoms, etc.). Temperature and top-p sampling control randomness and creativity, while tokenization converts text to/from model-understandable numerical tokens.

⚠️ Note: Running this model on CPU is slow; GPU is recommended for faster inference.

Trigger words

You should use medical report to trigger the image generation.

You should use symptoms to trigger the image generation.

You should use patient data to trigger the image generation.

You should use LLaMA to trigger the image generation.

You should use LoRA to trigger the image generation.

You should use health AI to trigger the image generation.

You should use clinical notes to trigger the image generation.

You should use disease prediction to trigger the image generation.

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