A LLM Inference server for Johnsnowlabs Medical LLM
2.6K
This Docker image provides a deployable inference server for medical large language models (LLMs) developed by JohnSnowLabs. Designed for healthcare and medical research applications, this service enables advanced medical AI capabilities with flexible deployment options.
| Model Name | Parameters | Total Memory | Max Sequence Length | Model Size | Max KV-Cache | Tensor Parallel Sizes |
|---|---|---|---|---|---|---|
| Medical-Visual-LLM-8B | 8B | ~25 GB | 262K | 17 GB | 8 GB | 1, 2, 4, 8 |
| Medical-LLM-14B | 14B | ~40 GB | 16K | 27 GB | 13 GB | 1, 2 |
| Medical-LLM-Small | 8B | ~25 GB | 262K | 17 GB | 8 GB | 1, 2, 4, 8 |
| Medical-LLM-Medium | 27B | ~66 GB | 262K | 50 GB | 16 GB | 2, 4, 8 |
| Medical-Reasoning-LLM-32B | 27B | ~66 GB | 262K | 50 GB | 16 GB | 2, 4, 8 |
| Medical-Spanish-LLM-24B | 24B | ~145 GB | 128K | 45 GB | 100 GB | 2, 4, 8 |
| Medical-Visual-LLM-30B | 30B | ~150 GB | 262K | 58 GB | 92 GB | 2, 4, 8 |
| Vision-OCR-LLM | 1B | ~6 GB | 32K | 2 GB | 4 GB | 1, 2, 4 |
| Vision-OCR-Structured-LLM | 7B | ~32 GB | 128K | 16 GB | 17 GB | 1, 2, 4 |
Note: Both
Vision-OCR-LLMandVision-OCR-Structured-LLMmust be run withtrust_remote_code=Truebecause their model implementations include custom code.
Important Notes
Memory Calculations: All memory calculations are based on half-precision (fp16/bf16) weights. Recommended GPU Memory considers the model size and the maximum key-value cache at the model's maximum sequence length. These calculations follow the guidelines from DJL's LMI Deployment Guide.ā
You can pull the image from š Docker Hubā :
docker pull johnsnowlabs/jsl-llms:latest
docker run -d \
--gpus all \
--env "SPARK_NLP_LICENSE=your_license_key" \
-p 8080:8080 \
--ipc=host \
johnsnowlabs/jsl-llms \
--model Medical-LLM-Small \
--port 8080
Mount a license.json file for more secure license management:
docker run -d \
--gpus all \
-v "$(pwd)/license.json:/app/license.json" \
-p 8080:8080 \
--ipc=host \
johnsnowlabs/jsl-llms \
--model Medical-LLM-Small \
--port 8080
For detailed information about available parameters and configuration options, please refer to the official VLLM documentation: š VLLM Server Parameters Documentationā
--tensor-parallel-size: Set number of GPUs for tensor parallelism--max-model-len: Maximum sequence length--gpu-memory-utilization: Fraction of GPU memory to be usedGET /health: Check service health statusGET /ping: Quick server pingGET /version: Retrieve server version information/v1/models/v1/chat/completionspayload = {
"model": "Medical-LLM-Small",
"messages": [
{"role": "system", "content": "You are a professional medical assistant"},
{"role": "user", "content": "Explain symptoms of chronic fatigue syndrome"}
],
"temperature": 0.7,
"max_tokens": 1024
}
/v1/completionspayload = {
"model": "Medical-LLM-Small",
"prompt": "Provide a detailed explanation of rheumatoid arthritis treatment",
"temperature": 0.7,
"max_tokens": 4096
}
For technical support, inquiries, or enterprise solutions, contact:
A valid Spark NLP license is required to use this inference server. Licenses can be obtained through JohnSnowLabs.
Content type
Image
Digest
sha256:280d5a61bā¦
Size
9.3 GB
Last updated
about 1 month ago
docker pull johnsnowlabs/jsl-llms