Instructions to use microsoft/biogpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/biogpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="microsoft/biogpt")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/biogpt") model = AutoModelForCausalLM.from_pretrained("microsoft/biogpt") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use microsoft/biogpt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "microsoft/biogpt" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "microsoft/biogpt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/microsoft/biogpt
- SGLang
How to use microsoft/biogpt 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 "microsoft/biogpt" \ --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": "microsoft/biogpt", "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 "microsoft/biogpt" \ --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": "microsoft/biogpt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use microsoft/biogpt with Docker Model Runner:
docker model run hf.co/microsoft/biogpt
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@@ -19,7 +19,7 @@ set a seed for reproducibility:
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>>> tokenizer = BioGptTokenizer.from_pretrained("microsoft/biogpt")
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>>> generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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>>> set_seed(42)
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>>> generator("COVID-19 is", max_length=
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[{'generated_text': 'COVID-19 is a disease that spreads worldwide and is currently found in a growing proportion of the population'},
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{'generated_text': 'COVID-19 is one of the largest viral epidemics in the world.'},
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{'generated_text': 'COVID-19 is a common condition affecting an estimated 1.1 million people in the United States alone.'},
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>>> tokenizer = BioGptTokenizer.from_pretrained("microsoft/biogpt")
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>>> generator = pipeline('text-generation', model=model, tokenizer=tokenizer)
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>>> set_seed(42)
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>>> generator("COVID-19 is", max_length=30, num_return_sequences=5)
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[{'generated_text': 'COVID-19 is a disease that spreads worldwide and is currently found in a growing proportion of the population'},
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{'generated_text': 'COVID-19 is one of the largest viral epidemics in the world.'},
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{'generated_text': 'COVID-19 is a common condition affecting an estimated 1.1 million people in the United States alone.'},
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