Instructions to use stabilityai/StableBeluga2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stabilityai/StableBeluga2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="stabilityai/StableBeluga2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("stabilityai/StableBeluga2") model = AutoModelForCausalLM.from_pretrained("stabilityai/StableBeluga2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use stabilityai/StableBeluga2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "stabilityai/StableBeluga2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stabilityai/StableBeluga2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/stabilityai/StableBeluga2
- SGLang
How to use stabilityai/StableBeluga2 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 "stabilityai/StableBeluga2" \ --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": "stabilityai/StableBeluga2", "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 "stabilityai/StableBeluga2" \ --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": "stabilityai/StableBeluga2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use stabilityai/StableBeluga2 with Docker Model Runner:
docker model run hf.co/stabilityai/StableBeluga2
How to finetune this beauty?
How can we finetune this? And could be the resources requirement for it.
How can we finetune this? And could be the resources requirement for it.
you fine tune it like a normal llm and keep in mind https://twitter.com/moinnadeem/status/1681393075367841792
and you will need 4,400 gigs of vram (with nothing to lower vram )
and you will need 4,400 gigs of vram (with nothing to lower vram )
But why? I thought LLAMA 2 can be fine-tuned with single A-100
and you will need 4,400 gigs of vram (with nothing to lower vram )
But why? I thought LLAMA 2 can be fine-tuned with single A-100
The 7b model yeah and the 13b model yeah with qlora but 70b model can't fine-tuned on a single gpu even with qlora