How to use from
SGLang
# Gated model: Login with a HF token with gated access permission
hf auth login
Install from pip and serve model
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "TaoMedAI/RareSeek-R1" \
    --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": "TaoMedAI/RareSeek-R1",
		"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 "TaoMedAI/RareSeek-R1" \
        --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": "TaoMedAI/RareSeek-R1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Quick Links

You need to agree to share your Hugging Face information to access this model

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

Log in or Sign Up to review the conditions and access this model content.

🧬 RareSeek-R1

A Specialized Language Model for Rare Disease Diagnosis and Clinical Reasoning

📖 Model Overview

RareSeek-R1 is a domain-specialized large language model tailored for rare-disease diagnostic reasoning, developed through a Progressive Parameter-Efficient Transfer Learning framework.

The model is first instruction-tuned on the clinically grounded RareMed-Corpus, a large, multi-source dataset deeply integrated from medical textbooks, guidelines, biomedical literature, and real-world EHR (Electronic Health Record) narratives. It is subsequently fine-tuned on RareMed-CoT, a high-fidelity corpus designed to instill explicit, stepwise clinical reasoning that aligns with real-world diagnostic workflows.

Figure 1: Overall framework and pipeline of RareSeek-R1. Figure 1: Overall framework and pipeline of RareSeek-R1.

🗄️ Dataset & Resources

📚 RareMedData: Access the comprehensive medical dataset used for training here:
👉 https://huggingface.co/datasets/TaoMedAI/RareMedData

Downloads last month
1
Safetensors
Model size
71B params
Tensor type
BF16
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for TaoMedAI/RareSeek-R1

Finetuned
(25)
this model