Text Generation
Transformers
Safetensors
English
code
helion-osc
mathematics
reasoning
algorithm
causal-lm
conversational
bitsandbytes
Instructions to use DeepXR/Helion-OSC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepXR/Helion-OSC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DeepXR/Helion-OSC") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DeepXR/Helion-OSC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DeepXR/Helion-OSC with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DeepXR/Helion-OSC" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DeepXR/Helion-OSC", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/DeepXR/Helion-OSC
- SGLang
How to use DeepXR/Helion-OSC 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 "DeepXR/Helion-OSC" \ --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": "DeepXR/Helion-OSC", "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 "DeepXR/Helion-OSC" \ --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": "DeepXR/Helion-OSC", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use DeepXR/Helion-OSC with Docker Model Runner:
docker model run hf.co/DeepXR/Helion-OSC
| version: '3.8' | |
| services: | |
| helion-osc-api: | |
| build: | |
| context: . | |
| dockerfile: Dockerfile | |
| container_name: helion-osc-api | |
| restart: unless-stopped | |
| ports: | |
| - "8000:8000" | |
| volumes: | |
| - ./models:/app/models | |
| - ./cache:/app/cache | |
| - ./outputs:/app/outputs | |
| environment: | |
| - CUDA_VISIBLE_DEVICES=0 | |
| - HF_HOME=/app/cache | |
| - TRANSFORMERS_CACHE=/app/cache | |
| deploy: | |
| resources: | |
| reservations: | |
| devices: | |
| - driver: nvidia | |
| count: 1 | |
| capabilities: [gpu] | |
| healthcheck: | |
| test: ["CMD", "curl", "-f", "http://localhost:8000/health"] | |
| interval: 30s | |
| timeout: 10s | |
| retries: 3 | |
| start_period: 60s | |
| networks: | |
| - helion-network | |
| # Optional: Nginx reverse proxy | |
| nginx: | |
| image: nginx:alpine | |
| container_name: helion-nginx | |
| restart: unless-stopped | |
| ports: | |
| - "80:80" | |
| - "443:443" | |
| volumes: | |
| - ./nginx.conf:/etc/nginx/nginx.conf:ro | |
| - ./ssl:/etc/nginx/ssl:ro | |
| depends_on: | |
| - helion-osc-api | |
| networks: | |
| - helion-network | |
| networks: | |
| helion-network: | |
| driver: bridge | |
| volumes: | |
| models: | |
| cache: | |
| outputs: |