Text Generation
Transformers
PEFT
English
gravityllm
spatial-audio
immersive-audio
spatial9
iamf
instruction-tuning
json
lora
qlora
Instructions to use Spatial9/GravityLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Spatial9/GravityLLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Spatial9/GravityLLM")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Spatial9/GravityLLM", dtype="auto") - PEFT
How to use Spatial9/GravityLLM with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Spatial9/GravityLLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Spatial9/GravityLLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Spatial9/GravityLLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Spatial9/GravityLLM
- SGLang
How to use Spatial9/GravityLLM 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 "Spatial9/GravityLLM" \ --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": "Spatial9/GravityLLM", "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 "Spatial9/GravityLLM" \ --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": "Spatial9/GravityLLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Spatial9/GravityLLM with Docker Model Runner:
docker model run hf.co/Spatial9/GravityLLM
| [project] | |
| name = "gravityllm" | |
| version = "0.1.0" | |
| description = "Constraint-driven Spatial9 scene generation for immersive audio." | |
| readme = "README.md" | |
| requires-python = ">=3.10" | |
| license = {text = "Apache-2.0"} | |
| dependencies = [ | |
| "accelerate>=0.31.0", | |
| "bitsandbytes>=0.43.0", | |
| "datasets>=2.19.0", | |
| "huggingface_hub>=0.24.0", | |
| "jsonschema>=4.22.0", | |
| "peft>=0.11.0", | |
| "safetensors>=0.4.3", | |
| "torch", | |
| "transformers>=4.41.0", | |
| ] | |
| [tool.setuptools] | |
| py-modules = ["train", "infer", "evaluate", "upload_to_hub"] | |