Instructions to use bobboyms/tynerox with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bobboyms/tynerox with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bobboyms/tynerox")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bobboyms/tynerox", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use bobboyms/tynerox with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bobboyms/tynerox" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bobboyms/tynerox", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bobboyms/tynerox
- SGLang
How to use bobboyms/tynerox 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 "bobboyms/tynerox" \ --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": "bobboyms/tynerox", "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 "bobboyms/tynerox" \ --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": "bobboyms/tynerox", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bobboyms/tynerox with Docker Model Runner:
docker model run hf.co/bobboyms/tynerox
| version: '3' | |
| services: | |
| mlflow: | |
| # image: ghcr.io/mlflow/mlflow:v2.21.3 | |
| # image: ghcr.io/mlflow/mlflow:v3.0.0rc0 | |
| build: . | |
| ports: | |
| - "5000:5000" | |
| environment: | |
| - MLFLOW_ARTIFACT_ROOT=s3://1hh-mlflow/artifacts | |
| - MLFLOW_TRACKING_URI=http://mlflow:5000 | |
| volumes: | |
| - ./mlflow:/mlflow | |
| command: mlflow server --host 0.0.0.0 --port 5000 --backend-store-uri sqlite:///mlflow.db --default-artifact-root s3://1hh-mlflow/artifacts | |
| # s3://1hh-mlflow/artifacts/ | |
| postgres: | |
| image: postgres:14 | |
| environment: | |
| - POSTGRES_USER=mlflow | |
| - POSTGRES_PASSWORD=mlflow | |
| - POSTGRES_DB=mlflowdb | |
| volumes: | |
| - ./postgres-temp:/var/lib/postgresql/temp | |
| # minio: | |
| # image: minio/minio:latest | |
| # ports: | |
| # - "9000:9000" | |
| # environment: | |
| # - MINIO_ROOT_USER=minioadmin | |
| # - MINIO_ROOT_PASSWORD=minioadmin | |
| # volumes: | |
| # - ./minio-temp:/temp | |
| # command: server /temp --console-address ":9001" | |
| nginx: | |
| image: nginx:latest | |
| ports: | |
| - "80:80" | |
| volumes: | |
| # - ./nginx.conf:/etc/nginx/nginx.conf:ro | |
| - ./nginx.conf:/etc/nginx/conf.d/default.conf:ro | |
| depends_on: | |
| - mlflow | |
| # - minio |