Instructions to use nferruz/ProtGPT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nferruz/ProtGPT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nferruz/ProtGPT2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nferruz/ProtGPT2") model = AutoModelForCausalLM.from_pretrained("nferruz/ProtGPT2") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nferruz/ProtGPT2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nferruz/ProtGPT2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nferruz/ProtGPT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nferruz/ProtGPT2
- SGLang
How to use nferruz/ProtGPT2 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 "nferruz/ProtGPT2" \ --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": "nferruz/ProtGPT2", "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 "nferruz/ProtGPT2" \ --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": "nferruz/ProtGPT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nferruz/ProtGPT2 with Docker Model Runner:
docker model run hf.co/nferruz/ProtGPT2
Finetune without using run_clm.py
#16
by TianlaiChen - opened
This comment has been hidden
Hi Leo,
I haven’t tried to fine-tune without the helper script but is definitely possible. I guess once you have defined tokenizer and model (which you do right) I would follow the tutorial. In this case you will have to create a txt file with your sequences, replacing the fasta headers with the endoftext tag. Then not sure how the tutorial does it, but you’ll have to tokenize, and define the splits (90/10?) for that dataset.
Hope this helps
Noelia
TianlaiChen changed discussion status to closed