Instructions to use AI4PD/ZymCTRL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4PD/ZymCTRL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AI4PD/ZymCTRL")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AI4PD/ZymCTRL") model = AutoModelForCausalLM.from_pretrained("AI4PD/ZymCTRL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AI4PD/ZymCTRL with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AI4PD/ZymCTRL" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AI4PD/ZymCTRL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AI4PD/ZymCTRL
- SGLang
How to use AI4PD/ZymCTRL 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/ZymCTRL" \ --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/ZymCTRL", "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/ZymCTRL" \ --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/ZymCTRL", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AI4PD/ZymCTRL with Docker Model Runner:
docker model run hf.co/AI4PD/ZymCTRL
Update README.md
Browse files
README.md
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for key,value in grouped_dataset.items():
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fn.write(value)
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fn.write("\n")
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fn.close()
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```
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The previous script will prepare a text file with the correct format for tokenization.
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Now we can use the tokenizer to convert its contents to tokens.
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for key,value in grouped_dataset.items():
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fn.write(value)
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fn.write("\n")
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fn.close()
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fn = open("./2.7.3.13_processed.txt",'w')
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for key,value in grouped_dataset.items():
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padding_len = 1024 - len(tokenizer(value)['input_ids'])
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padding = "<pad>"*padding_len
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print(len(tokenizer(value+padding)['input_ids']))
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fn.write(value+padding)
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fn.write
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fn.write("\n")
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fn.close()
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```
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The previous script will prepare a text file with the correct format for tokenization.
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Now we can use the tokenizer to convert its contents to tokens.
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