Text Generation
Transformers
TensorBoard
Safetensors
biology
genomics
rna
sequence-generation
regression
reinforcement-learning
git-lfs
Instructions to use JoyXiangLab/rnaseek-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoyXiangLab/rnaseek-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="JoyXiangLab/rnaseek-full")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JoyXiangLab/rnaseek-full", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use JoyXiangLab/rnaseek-full with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "JoyXiangLab/rnaseek-full" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "JoyXiangLab/rnaseek-full", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/JoyXiangLab/rnaseek-full
- SGLang
How to use JoyXiangLab/rnaseek-full 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 "JoyXiangLab/rnaseek-full" \ --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": "JoyXiangLab/rnaseek-full", "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 "JoyXiangLab/rnaseek-full" \ --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": "JoyXiangLab/rnaseek-full", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use JoyXiangLab/rnaseek-full with Docker Model Runner:
docker model run hf.co/JoyXiangLab/rnaseek-full
| name: rnaseek | |
| channels: | |
| - defaults | |
| - conda-forge | |
| - bioconda | |
| dependencies: | |
| - python=3.11 | |
| - pip | |
| - setuptools | |
| - wheel | |
| - packaging | |
| - ninja | |
| - pybind11 | |
| - pytorch=2.10.0=gpu_cuda128_py311* | |
| - torchvision=0.25.0=cuda128py311* | |
| - torchaudio=2.10.0=cuda128py311* | |
| - pip: | |
| - flash-attn==2.6.3 | |
| - torchcodec==0.10.0 | |
| - numpy==2.3.5 | |
| - pandas | |
| - scipy==1.16.3 | |
| - scikit-learn==1.7.2 | |
| - matplotlib==3.10.7 | |
| - seaborn==0.13.2 | |
| - biopython==1.86 | |
| - cutadapt | |
| - multiqc | |
| - pysam==0.23.3 | |
| - h5py==3.16.0 | |
| - openpyxl==3.1.5 | |
| - statsmodels==0.14.6 | |
| - numba==0.62.1 | |
| - pyarrow==21.0.0 | |
| - ipykernel | |
| - ipywidgets==8.1.8 | |
| - accelerate==1.13.0 | |
| - transformers==5.5.4 | |
| - datasets==4.8.4 | |
| - peft==0.18.1 | |
| - trl==1.0.0 | |
| - bitsandbytes==0.48.2 | |
| - safetensors==0.5.3 | |
| - sentencepiece==0.2.1 | |
| - tokenizers==0.22.1 | |
| - tensorboard==2.20.0 | |
| - fastapi==0.123.10 | |
| - uvicorn==0.38.0 | |
| - pydantic | |
| - psutil | |
| - requests | |
| - tqdm | |
| - ViennaRNA==2.7.0 | |
| - logomaker==0.8.7 | |
| - umap-learn==0.5.11 | |
| - anndata==0.12.10 | |
| - pydeseq2==0.5.4 | |
| - zarr==3.1.6 | |
| - librosa==0.11.0 | |
| - audiomentations==0.43.1 | |
| - soundfile==0.13.1 | |
| - soxr==0.5.0.post1 | |