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: docker | |
| on: | |
| workflow_dispatch: | |
| push: | |
| branches: | |
| - "main" | |
| paths: | |
| - "**/*.py" | |
| - "pyproject.toml" | |
| - "docker/**" | |
| - ".github/workflows/*.yml" | |
| pull_request: | |
| branches: | |
| - "main" | |
| paths: | |
| - "**/*.py" | |
| - "pyproject.toml" | |
| - "docker/**" | |
| - ".github/workflows/*.yml" | |
| release: | |
| types: | |
| - published | |
| jobs: | |
| build: | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| include: | |
| - device: "cuda" | |
| runs-on: ubuntu-latest | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.ref }}-${{ matrix.device }} | |
| cancel-in-progress: ${{ github.ref != 'refs/heads/main' }} | |
| environment: | |
| name: docker | |
| url: https://hub.docker.com/r/hiyouga/llamafactory | |
| steps: | |
| - name: Free up disk space | |
| uses: jlumbroso/free-disk-space@v1.3.1 | |
| with: | |
| tool-cache: true | |
| docker-images: false | |
| - name: Checkout | |
| uses: actions/checkout@v6 | |
| - name: Get llamafactory version | |
| id: version | |
| run: | | |
| if [ "${{ github.event_name }}" = "release" ]; then | |
| echo "tag=$(grep -oP 'VERSION = "\K[^"]+' src/llamafactory/extras/env.py)" >> "$GITHUB_OUTPUT" | |
| else | |
| echo "tag=latest" >> "$GITHUB_OUTPUT" | |
| fi | |
| - name: Set up Docker Buildx | |
| uses: docker/setup-buildx-action@v3 | |
| - name: Login to Docker Hub | |
| if: ${{ github.event_name != 'pull_request' }} | |
| uses: docker/login-action@v3 | |
| with: | |
| username: ${{ vars.DOCKERHUB_USERNAME }} | |
| password: ${{ secrets.DOCKERHUB_TOKEN }} | |
| - name: Build and push Docker image (CUDA) | |
| if: ${{ matrix.device == 'cuda' }} | |
| uses: docker/build-push-action@v6 | |
| with: | |
| context: . | |
| file: ./docker/docker-cuda/Dockerfile | |
| push: ${{ github.event_name != 'pull_request' }} | |
| tags: | | |
| docker.io/hiyouga/llamafactory:${{ steps.version.outputs.tag }} | |