Instructions to use Danielbrdz/MedBarcenas-4b-Hemodialisis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Danielbrdz/MedBarcenas-4b-Hemodialisis with Transformers:

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

pipe = pipeline("image-text-to-text", model="Danielbrdz/MedBarcenas-4b-Hemodialisis")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Danielbrdz/MedBarcenas-4b-Hemodialisis")
model = AutoModelForMultimodalLM.from_pretrained("Danielbrdz/MedBarcenas-4b-Hemodialisis", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Danielbrdz/MedBarcenas-4b-Hemodialisis with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Danielbrdz/MedBarcenas-4b-Hemodialisis"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Danielbrdz/MedBarcenas-4b-Hemodialisis",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/Danielbrdz/MedBarcenas-4b-Hemodialisis

SGLang

How to use Danielbrdz/MedBarcenas-4b-Hemodialisis 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 "Danielbrdz/MedBarcenas-4b-Hemodialisis" \
    --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": "Danielbrdz/MedBarcenas-4b-Hemodialisis",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "Danielbrdz/MedBarcenas-4b-Hemodialisis" \
        --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": "Danielbrdz/MedBarcenas-4b-Hemodialisis",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use Danielbrdz/MedBarcenas-4b-Hemodialisis with Docker Model Runner:
```
docker model run hf.co/Danielbrdz/MedBarcenas-4b-Hemodialisis
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

MedBarcenas 4b Hemodiálisis

Badado en MedGemma 4b it de Google

Entrado con el dataset propio Danielbrdz/MedBarcenas-Hemodialisis

El objetivo de este LLM es responder preguntas básicas de hemodiálisis en español

Aún este LLM está algo verde en muchas cuestiones, espero yo lanzar un modelo Pro con conocimiento ampliado y poder predecir quién corre mayor riesgo de hospitalización o de saltarse un tratamiento, pero claro siempre el doctor debe tomar la última decisión

Badado in Google MedGemma 4b it

Entered with own dataset Danielbrdz/MedBarcenas-Hemodialisis

The goal of this LLM is to answer basic hemodialysis questions in Spanish.

This LLM is still a bit green in many questions, I hope to launch a Pro model with extended knowledge and be able to predict who is at higher risk of hospitalization or skipping a treatment, but of course the doctor should always make the final decision.

Made with ❤️ in Guadalupe, Nuevo Leon, Mexico 🇲🇽