Text Generation
Transformers
Safetensors
Arabic
qwen
llama-factory
lora
arabic
question-answering
instruction-tuning
kaggle
fine-tuned
conversational
Instructions to use youssefedweqd/working with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use youssefedweqd/working with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="youssefedweqd/working") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("youssefedweqd/working", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use youssefedweqd/working with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "youssefedweqd/working" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "youssefedweqd/working", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/youssefedweqd/working
- SGLang
How to use youssefedweqd/working 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 "youssefedweqd/working" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "youssefedweqd/working", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "youssefedweqd/working" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "youssefedweqd/working", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use youssefedweqd/working with Docker Model Runner:
docker model run hf.co/youssefedweqd/working
| name: docker | |
| on: | |
| workflow_dispatch: | |
| push: | |
| branches: | |
| - "main" | |
| paths: | |
| - "**/*.py" | |
| - "requirements.txt" | |
| - "docker/**" | |
| - ".github/workflows/*.yml" | |
| pull_request: | |
| branches: | |
| - "main" | |
| paths: | |
| - "**/*.py" | |
| - "requirements.txt" | |
| - "docker/**" | |
| - ".github/workflows/*.yml" | |
| jobs: | |
| build: | |
| runs-on: ubuntu-latest | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.ref }} | |
| cancel-in-progress: ${{ github.ref != 'refs/heads/main' }} | |
| environment: | |
| name: docker | |
| url: https://hub.docker.com/r/hiyouga/llamafactory | |
| steps: | |
| - name: Free up disk space | |
| run: | | |
| df -h | |
| sudo rm -rf /usr/share/dotnet | |
| sudo rm -rf /opt/ghc | |
| sudo rm -rf /opt/hostedtoolcache | |
| df -h | |
| - name: Checkout | |
| uses: actions/checkout@v4 | |
| - name: Set up Python | |
| uses: actions/setup-python@v5 | |
| with: | |
| python-version: "3.9" | |
| - name: Get llamafactory version | |
| id: version | |
| run: | | |
| echo "tag=$(python setup.py --version | sed 's/\.dev0//')" >> "$GITHUB_OUTPUT" | |
| - 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 | |
| uses: docker/build-push-action@v6 | |
| with: | |
| context: . | |
| file: ./docker/docker-cuda/Dockerfile | |
| build-args: | | |
| EXTRAS=metrics,deepspeed,liger-kernel | |
| push: ${{ github.event_name != 'pull_request' }} | |
| tags: | | |
| docker.io/hiyouga/llamafactory:latest | |
| docker.io/hiyouga/llamafactory:${{ steps.version.outputs.tag }} | |
| cache-from: type=gha | |
| cache-to: type=gha,mode=max | |