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
RuntimeError: shape '[1, 60, 64, 128]' is invalid for input of size 61440
I have been trying to use the example, so far I have ended up with the following error
File ~/anaconda3/envs/triton/lib/python3.11/site-packages/transformers/models/llama/modeling_llama.py:261 in forward
key_states = self.k_proj(hidden_states).view(bsz, q_len, self.num_heads, self.head_dim).transpose(1, 2)
RuntimeError: shape '[1, 60, 64, 128]' is invalid for input of size 61440
The issue is generally with the transformers version. You will need transformers>=4.31.0 to make this work.
Thanks. Seemed to be the problem
How to slove it
How to slove it
The issue is generally with the transformers version. You will need transformers>=4.31.0 to make this work.
I upgrade transformer 4.31.0 ,but didn't slove
and one strange problem , 7b or 13b can work ,but 70B failed
have the same issue with the 70B version of models
You also need python>=3.8 to address this issue.
Same issue (but on Llama-3-8B model)
python=3.9 and transformers==4.41.0 don't work :/
Any Solution ?
model: 'meta-llama/Meta-Llama-3-8B-Instruct'
using Tesla K8
Cuda 11.6 Nvidia 470 drivers
pip install torch==1.12.0+cu116 torchvision==0.13.0+cu116 torchaudio==0.12.0+cu116 -f https://download.pytorch.org/whl/cu116/torch_stable.html
pip install -r requirements.txt
requirements.txt:
transformers==4.31.0 # For working with Meta LLaMA and BitsAndBytesConfig
accelerate==0.21.0 # For multi-GPU handling and model acceleration
bitsandbytes==0.38.1 # For 8-bit quantization
scipy==1.9.3
It works fine.