Instructions to use samarth1029/Gemma-2-2b-baymax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use samarth1029/Gemma-2-2b-baymax with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="samarth1029/Gemma-2-2b-baymax")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("samarth1029/Gemma-2-2b-baymax")
model = AutoModelForMultimodalLM.from_pretrained("samarth1029/Gemma-2-2b-baymax")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use samarth1029/Gemma-2-2b-baymax with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "samarth1029/Gemma-2-2b-baymax"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "samarth1029/Gemma-2-2b-baymax",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/samarth1029/Gemma-2-2b-baymax

SGLang

How to use samarth1029/Gemma-2-2b-baymax with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "samarth1029/Gemma-2-2b-baymax" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "samarth1029/Gemma-2-2b-baymax",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "samarth1029/Gemma-2-2b-baymax" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "samarth1029/Gemma-2-2b-baymax",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use samarth1029/Gemma-2-2b-baymax with Docker Model Runner:
```
docker model run hf.co/samarth1029/Gemma-2-2b-baymax
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

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Model Card for Model ID

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

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]

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

Uses

Recommendations

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

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

Downloads last month: -

Safetensors

Model size

3B params

Tensor type

F16

Model tree for samarth1029/Gemma-2-2b-baymax

Base model

google/gemma-2-2b

Finetuned

google/gemma-2-2b-it

Finetuned

(953)

this model

Quantizations

2 models

samarth1029
/

Gemma-2-2b-baymax