Instructions to use PharMolix/BioMedGPT-LM-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PharMolix/BioMedGPT-LM-7B with Transformers:

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

pipe = pipeline("text-generation", model="PharMolix/BioMedGPT-LM-7B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("PharMolix/BioMedGPT-LM-7B")
model = AutoModelForCausalLM.from_pretrained("PharMolix/BioMedGPT-LM-7B", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use PharMolix/BioMedGPT-LM-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "PharMolix/BioMedGPT-LM-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PharMolix/BioMedGPT-LM-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/PharMolix/BioMedGPT-LM-7B

SGLang

How to use PharMolix/BioMedGPT-LM-7B 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 "PharMolix/BioMedGPT-LM-7B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PharMolix/BioMedGPT-LM-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "PharMolix/BioMedGPT-LM-7B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "PharMolix/BioMedGPT-LM-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use PharMolix/BioMedGPT-LM-7B with Docker Model Runner:
```
docker model run hf.co/PharMolix/BioMedGPT-LM-7B
```

youngking0727 commited on Aug 12, 2023

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1 Parent(s): e9c1b06

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@@ -34,7 +34,10 @@ PharMolix
 ### How to Use
 BioMedGPT-LM-7B is a part of **[BioMedGPT-10B](https://github.com/BioFM/OpenBioMed)**, an open-source version of BioMedGPT. BioMedGPT is a multimodal generative pre-trained transformer (GPT) for biomedicine, which bridges the natural language modality and diverse biomed-
 ical data modalities via a single GPT model. BioMedGPT aligns different biological modalities with the text modality via BioMedGPT-LM. The details of BioMedGPT-10B and BioMedGPT-LM-7B can be found in the [technical report]().
-![](BioMedGPT-10B.jpeg)
 **Intended Use Cases**

 ### How to Use
 BioMedGPT-LM-7B is a part of **[BioMedGPT-10B](https://github.com/BioFM/OpenBioMed)**, an open-source version of BioMedGPT. BioMedGPT is a multimodal generative pre-trained transformer (GPT) for biomedicine, which bridges the natural language modality and diverse biomed-
 ical data modalities via a single GPT model. BioMedGPT aligns different biological modalities with the text modality via BioMedGPT-LM. The details of BioMedGPT-10B and BioMedGPT-LM-7B can be found in the [technical report]().
+![The architecture of BioMedGPT-10B](BioMedGPT-10B.jpeg)
 **Intended Use Cases**