Text Generation
Transformers
Safetensors
gpt_neox
antibodies
protein
drug discovery
text-generation-inference
How to use from
SGLangUse 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 "ollieturnbull/p-IgGen" \
--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": "ollieturnbull/p-IgGen",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
Model Card for Model ID
Auto-regressive protein language model for paired antibody library generation.
Pretrained on unpaired heavy and light chain sequences from the Observed Antibody Space (OAS), and finetuned on paired sequences.
Model Details
Model Description
- Funded by: EPSRC, AstraZeneca
- License: BSD-3-Clause license
Model Sources
- Downloads last month
- 3,635
Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "ollieturnbull/p-IgGen" \ --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": "ollieturnbull/p-IgGen", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'