Instructions to use texdata/Vran-27B-SLO-BioMed-Research with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use texdata/Vran-27B-SLO-BioMed-Research with Transformers:

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

pipe = pipeline("text-generation", model="texdata/Vran-27B-SLO-BioMed-Research")
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)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("texdata/Vran-27B-SLO-BioMed-Research")
model = AutoModelForMultimodalLM.from_pretrained("texdata/Vran-27B-SLO-BioMed-Research", 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=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use texdata/Vran-27B-SLO-BioMed-Research with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "texdata/Vran-27B-SLO-BioMed-Research"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "texdata/Vran-27B-SLO-BioMed-Research",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/texdata/Vran-27B-SLO-BioMed-Research

SGLang

How to use texdata/Vran-27B-SLO-BioMed-Research 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 "texdata/Vran-27B-SLO-BioMed-Research" \
    --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": "texdata/Vran-27B-SLO-BioMed-Research",
		"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 "texdata/Vran-27B-SLO-BioMed-Research" \
        --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": "texdata/Vran-27B-SLO-BioMed-Research",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use texdata/Vran-27B-SLO-BioMed-Research with Docker Model Runner:
```
docker model run hf.co/texdata/Vran-27B-SLO-BioMed-Research
```

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This repository is publicly accessible, but you have to accept the conditions to access its files and content.

By requesting access you acknowledge that Vran is an experimental RESEARCH language model with NO medical intended purpose. It is not a medical device (EU MDR), is not CE/FDA-cleared, and is not for diagnosis, treatment, triage, prescribing, clinical decision-making, or patient care. You agree to use it only for research and non-commercial purposes, not to deploy it as a clinical or "health assistant", and you accept sole responsibility for compliance with applicable law (EU AI Act, GDPR, EU MDR). Provided AS IS, without warranty; the authors accept no liability.

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