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AI4PD
/
ZymCTRL

Text Generation
Transformers
PyTorch
gpt2
biology
text-generation-inference
Model card Files Files and versions
xet
Community
17

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")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • 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
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Adding `safetensors` variant of this model

#17 opened about 1 year ago by
SFconvertbot

Are you releasing the dataset?

1
#15 opened over 1 year ago by
paraschopra

Adding `safetensors` variant of this model

#14 opened over 1 year ago by
SFconvertbot

Adding `safetensors` variant of this model

#12 opened over 1 year ago by
SFconvertbot

Finetuned model generates sequences far different from sequences in the finetune training set

1
#11 opened over 1 year ago by
atqamar

Many generated sequences are highly similar to WT sequences

1
#10 opened over 2 years ago by
ShanGao

Hit handling for bulk generation

❤️ 1
#9 opened over 2 years ago by
fmoorhof

Adding `safetensors` variant of this model

#8 opened almost 3 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#7 opened almost 3 years ago by
SFconvertbot

fine-tuning the model with orphan sequences

1
#6 opened almost 3 years ago by
rqh

Example 2: Fine-tuning on a set of user-defined sequences

2
#5 opened about 3 years ago by
ipark

Can we do the inferences on ZymCTRL with multi GPUs?

2
#4 opened about 3 years ago by
guruace

Adding `safetensors` variant of this model

#3 opened about 3 years ago by
SFconvertbot

Fine-tuning memory and custom tokenizer

2
#2 opened about 3 years ago by
ipark
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