Text Generation
Transformers
Safetensors
mixtral
biology
protein-language-model
protein-generation
causal-lm
mixture-of-experts
text-generation-inference
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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
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README.md
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ProtGPT3-10B is a single-sequence autoregressive protein language model for protein sequence generation. It is the largest model in the [ProtGPT3 family](https://huggingface.co/collections/AI4PD/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.
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For more info and guidance how to generate sequences with ProtGPT3-10B check out the extensive description provided in [ProtGPT3-1.3B](https://huggingface.co/AI4PD/ProtGPT3-1.3B), just replacing the model name (i.e., `model_name=AI4PD/ProtGPT3-10B`).
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Also consider using the [ProtGPT3-10B-dpo](https://huggingface.co/AI4PD/ProtGPT3-10B-dpo) version for an equivalent model size, but with improved sequence generation.
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## More Information
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All models and code are released through the Hugging Face ecosystem and accompanying code repository.
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For guidance how to generate sequences with ProtGPT3-10B check out the extensive description provided in [ProtGPT3-1.3B](https://huggingface.co/AI4PD/ProtGPT3-1.3B).
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ProtGPT3-10B is a single-sequence autoregressive protein language model for protein sequence generation. It is the largest model in the [ProtGPT3 family](https://huggingface.co/collections/AI4PD/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.
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For more info and guidance on how to generate sequences with ProtGPT3-10B check out the extensive description provided in [ProtGPT3-1.3B](https://huggingface.co/AI4PD/ProtGPT3-1.3B), just replacing the model name (i.e., `model_name=AI4PD/ProtGPT3-10B`).
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Also consider using the [ProtGPT3-10B-dpo](https://huggingface.co/AI4PD/ProtGPT3-10B-dpo) version for an equivalent model size, but with improved sequence generation.
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```
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## More Information
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For guidance on how to generate sequences with ProtGPT3-10B check out the extensive description provided in [ProtGPT3-1.3B](https://huggingface.co/AI4PD/ProtGPT3-1.3B).
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All models and code are released through the Hugging Face ecosystem and accompanying code repository.
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