Instructions to use BlueZeros/EHR-R1-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BlueZeros/EHR-R1-8B with Transformers:

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

pipe = pipeline("text-generation", model="BlueZeros/EHR-R1-8B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("BlueZeros/EHR-R1-8B")
model = AutoModelForCausalLM.from_pretrained("BlueZeros/EHR-R1-8B")
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

vLLM

How to use BlueZeros/EHR-R1-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "BlueZeros/EHR-R1-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BlueZeros/EHR-R1-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/BlueZeros/EHR-R1-8B

SGLang

How to use BlueZeros/EHR-R1-8B 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 "BlueZeros/EHR-R1-8B" \
    --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": "BlueZeros/EHR-R1-8B",
		"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 "BlueZeros/EHR-R1-8B" \
        --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": "BlueZeros/EHR-R1-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use BlueZeros/EHR-R1-8B with Docker Model Runner:
```
docker model run hf.co/BlueZeros/EHR-R1-8B
```

Enhance model card with metadata, paper link, code link, and usage example

by nielsr HF Staff - opened Nov 1, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+127

-3

nielsr

Nov 1, 2025

This PR significantly improves the model card for EHR-R1 by:

Adding pipeline_tag: text-generation to improve discoverability on the Hugging Face Hub.
Including library_name: transformers metadata, which enables the automated "how to use" widget and provides immediate code snippets for users.
Linking to the official paper: EHR-R1: A Reasoning-Enhanced Foundational Language Model for Electronic Health Record Analysis.
Providing a direct link to the GitHub repository: https://github.com/MAGIC-AI4Med/EHR-R1.
Incorporating a detailed model description, key highlights, and a practical transformers code snippet for inference, all sourced directly from the GitHub README. The EHR input format is also included to guide users.

This update makes the model more accessible, discoverable, and user-friendly for the community.

Enhance model card with metadata, paper link, code link, and usage examplee88929cb

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

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README.md

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