Text Generation
Transformers
Safetensors
llama
research
code
mathematics
reasoning
multilingual
long-context
custom_code
text-generation-inference
Instructions to use DeepXR/Helion-V2.5-Rnd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepXR/Helion-V2.5-Rnd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DeepXR/Helion-V2.5-Rnd", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DeepXR/Helion-V2.5-Rnd", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("DeepXR/Helion-V2.5-Rnd", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use DeepXR/Helion-V2.5-Rnd with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DeepXR/Helion-V2.5-Rnd" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DeepXR/Helion-V2.5-Rnd", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DeepXR/Helion-V2.5-Rnd
- SGLang
How to use DeepXR/Helion-V2.5-Rnd 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-V2.5-Rnd" \ --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": "DeepXR/Helion-V2.5-Rnd", "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 "DeepXR/Helion-V2.5-Rnd" \ --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": "DeepXR/Helion-V2.5-Rnd", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DeepXR/Helion-V2.5-Rnd with Docker Model Runner:
docker model run hf.co/DeepXR/Helion-V2.5-Rnd
| version: '3.8' | |
| services: | |
| helion-inference: | |
| build: | |
| context: . | |
| dockerfile: Dockerfile | |
| args: | |
| - CUDA_VERSION=12.1.1 | |
| image: helion:2.5-rnd | |
| container_name: helion-inference-server | |
| deploy: | |
| resources: | |
| reservations: | |
| devices: | |
| - driver: nvidia | |
| count: all | |
| capabilities: [gpu] | |
| environment: | |
| - MODEL_PATH=/models/helion | |
| - MODEL_NAME=DeepXR/Helion-2.5-Rnd | |
| - PORT=8000 | |
| - HOST=0.0.0.0 | |
| - TENSOR_PARALLEL_SIZE=2 | |
| - MAX_MODEL_LEN=131072 | |
| - GPU_MEMORY_UTILIZATION=0.95 | |
| - CUDA_VISIBLE_DEVICES=0,1 | |
| - WORKERS=1 | |
| # Optional: HuggingFace token for private models | |
| # - HF_TOKEN=your_token_here | |
| # Logging | |
| - LOG_LEVEL=info | |
| - LOG_FILE=/app/logs/helion.log | |
| volumes: | |
| - ./models:/models:ro | |
| - ./logs:/app/logs | |
| - ./cache:/app/cache | |
| - ./inference:/app/inference:ro | |
| - ./model_config.yaml:/app/model_config.yaml:ro | |
| ports: | |
| - "8000:8000" | |
| - "8001:8001" # Metrics | |
| - "8002:8002" # Admin | |
| healthcheck: | |
| test: ["CMD", "curl", "-f", "http://localhost:8000/health"] | |
| interval: 30s | |
| timeout: 10s | |
| retries: 3 | |
| start_period: 120s | |
| restart: unless-stopped | |
| networks: | |
| - helion-network | |
| logging: | |
| driver: "json-file" | |
| options: | |
| max-size: "100m" | |
| max-file: "10" | |
| prometheus: | |
| image: prom/prometheus:latest | |
| container_name: helion-prometheus | |
| volumes: | |
| - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml:ro | |
| - prometheus-data:/prometheus | |
| ports: | |
| - "9090:9090" | |
| command: | |
| - '--config.file=/etc/prometheus/prometheus.yml' | |
| - '--storage.tsdb.path=/prometheus' | |
| - '--web.console.libraries=/usr/share/prometheus/console_libraries' | |
| - '--web.console.templates=/usr/share/prometheus/consoles' | |
| networks: | |
| - helion-network | |
| restart: unless-stopped | |
| grafana: | |
| image: grafana/grafana:latest | |
| container_name: helion-grafana | |
| environment: | |
| - GF_SECURITY_ADMIN_PASSWORD=admin | |
| - GF_USERS_ALLOW_SIGN_UP=false | |
| volumes: | |
| - grafana-data:/var/lib/grafana | |
| - ./monitoring/grafana/dashboards:/etc/grafana/provisioning/dashboards:ro | |
| - ./monitoring/grafana/datasources:/etc/grafana/provisioning/datasources:ro | |
| ports: | |
| - "3000:3000" | |
| networks: | |
| - helion-network | |
| depends_on: | |
| - prometheus | |
| restart: unless-stopped | |
| nginx: | |
| image: nginx:alpine | |
| container_name: helion-nginx | |
| volumes: | |
| - ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro | |
| - ./nginx/ssl:/etc/nginx/ssl:ro | |
| ports: | |
| - "80:80" | |
| - "443:443" | |
| networks: | |
| - helion-network | |
| depends_on: | |
| - helion-inference | |
| restart: unless-stopped | |
| redis: | |
| image: redis:7-alpine | |
| container_name: helion-redis | |
| command: redis-server --appendonly yes | |
| volumes: | |
| - redis-data:/data | |
| ports: | |
| - "6379:6379" | |
| networks: | |
| - helion-network | |
| restart: unless-stopped | |
| networks: | |
| helion-network: | |
| driver: bridge | |
| ipam: | |
| config: | |
| - subnet: 172.28.0.0/16 | |
| volumes: | |
| prometheus-data: | |
| driver: local | |
| grafana-data: | |
| driver: local | |
| redis-data: | |
| driver: local |