Text Generation
Transformers
Safetensors
veyra
causal-lm
custom-code
research
architecture-preview
stablecoherence
recursive-transformer
custom_code
Instructions to use north-previews/Veyra-Next-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use north-previews/Veyra-Next-Preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="north-previews/Veyra-Next-Preview", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("north-previews/Veyra-Next-Preview", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use north-previews/Veyra-Next-Preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "north-previews/Veyra-Next-Preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "north-previews/Veyra-Next-Preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/north-previews/Veyra-Next-Preview
- SGLang
How to use north-previews/Veyra-Next-Preview 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 "north-previews/Veyra-Next-Preview" \ --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": "north-previews/Veyra-Next-Preview", "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 "north-previews/Veyra-Next-Preview" \ --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": "north-previews/Veyra-Next-Preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use north-previews/Veyra-Next-Preview with Docker Model Runner:
docker model run hf.co/north-previews/Veyra-Next-Preview
Download function-runtime.json from north-previews/Veyra-Next-Preview: direct link, hf CLI and curl.
- Browser
- Download file 165 Bytes
-
https://huggingface.co/north-previews/Veyra-Next-Preview/resolve/main/function-runtime.json
- Command line
-
hf download hf://north-previews/Veyra-Next-Preview/function-runtime.json
-
curl -L -o function-runtime.json https://huggingface.co/north-previews/Veyra-Next-Preview/resolve/main/function-runtime.json
165 Bytes
| {"elapsed_seconds": 765.9413354559999, "hard_timeout_seconds": 3000, "startup_timeout_seconds": 120, "gpu": "H100", "cpu_max": 2, "memory_max_gib": 16, "retries": 0} |