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
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