Instructions to use opig/p-IgGen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opig/p-IgGen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="opig/p-IgGen")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("opig/p-IgGen") model = AutoModelForCausalLM.from_pretrained("opig/p-IgGen") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use opig/p-IgGen with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "opig/p-IgGen" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "opig/p-IgGen", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/opig/p-IgGen
- SGLang
How to use opig/p-IgGen 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 "opig/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": "opig/p-IgGen", "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 "opig/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": "opig/p-IgGen", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use opig/p-IgGen with Docker Model Runner:
docker model run hf.co/opig/p-IgGen
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.
Getting Started?
This model was featured in the Hugging Face blog How to Train an Antibody Developability Model (found here: https://huggingface.co/blog/ginkgo-datapoints/making-antibody-embeddings-and-predictions). Sample code on how to get started using this model can be found in the blog.
Model Details
Model Description
- Funded by: EPSRC, AstraZeneca
- License: BSD-3-Clause license
Model Sources
Note: This is a duplicate of Ollie Turnbull's model repo, found here: https://huggingface.co/ollieturnbull/p-IgGen
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