Instructions to use AI4PD/ProtGPT3-10B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4PD/ProtGPT3-10B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AI4PD/ProtGPT3-10B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AI4PD/ProtGPT3-10B") model = AutoModelForCausalLM.from_pretrained("AI4PD/ProtGPT3-10B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use AI4PD/ProtGPT3-10B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AI4PD/ProtGPT3-10B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AI4PD/ProtGPT3-10B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AI4PD/ProtGPT3-10B
- SGLang
How to use AI4PD/ProtGPT3-10B 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 "AI4PD/ProtGPT3-10B" \ --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": "AI4PD/ProtGPT3-10B", "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 "AI4PD/ProtGPT3-10B" \ --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": "AI4PD/ProtGPT3-10B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AI4PD/ProtGPT3-10B with Docker Model Runner:
docker model run hf.co/AI4PD/ProtGPT3-10B
Model Card for ProtGPT3-1OB
Model Description
ProtGPT3-10B is a single-sequence autoregressive protein language model for protein sequence generation. It is the largest model in the ProtGPT3 family, an open-source suite of promptable and aligned protein language models ranging from 112M to 10B parameters. ProtGPT3 models use a causal Mixtral-style Mixture-of-Experts architecture and are trained for causal language modeling on protein sequences.
For more info and guidance on how to generate sequences with ProtGPT3-10B check out the extensive description provided in ProtGPT3-1.3B, just replacing the model name (i.e., model_name=AI4PD/ProtGPT3-10B).
Also consider using the ProtGPT3-10B-dpo version for an equivalent model size, but with improved sequence generation.
Out-of-Scope Use
The model should not be used as the sole basis for experimental, clinical, environmental, or safety-critical decisions. Generated proteins require downstream computational and experimental validation. The model is not guaranteed to generate functional, soluble, safe, or synthesizable proteins.
Bias, Risks, and Limitations
ProtGPT3-1OB learns from public protein sequence datasets and may reproduce biases present in those datasets. Generated sequences may be low-complexity, nonfunctional, unstable, insoluble, or biologically implausible. Protein generation models may also present dual-use risks if used irresponsibly.
Citation
BibTeX:
@article{protgpt3,
title={ProtGPT3: an Open-source family of Promptable and Aligned Protein Language Models},
author={Anonymous Authors},
year={2026}
}
More Information
For guidance on how to generate sequences with ProtGPT3-10B check out the extensive description provided in ProtGPT3-1.3B. All models and code are released through the Hugging Face ecosystem and accompanying code repository.
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