---
base_model:
- google/gemma-2-2b-it
datasets:
- lavita/ChatDoctor-HealthCareMagic-100k
library_name: transformers
pipeline_tag: text-generation
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->
Baymax is a conversational AI model built specifically to help answer patient questions about health concerns. It’s based on Gemma-2B-IT but fine-tuned with real doctor-patient conversation data, so it’s trained to understand the context and sensitivities of medical discussions. The goal with Baymax is to create a model that’s not just informative, but also empathetic—providing answers that feel supportive and helpful, just like a real conversation with a healthcare provider.


## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** [Samarth Mishra]
- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [More Information Needed]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** [google-gemma-2-2b-it]

### Model Sources [optional]

<!-- Provide the basic links for the model. -->

- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]

## Uses

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

## Training Details

### Training Data

<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

[https://huggingface.co/datasets/lavita/ChatDoctor-HealthCareMagic-100k]