Instructions to use jetmoe/jetmoe-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jetmoe/jetmoe-8b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jetmoe/jetmoe-8b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jetmoe/jetmoe-8b") model = AutoModelForCausalLM.from_pretrained("jetmoe/jetmoe-8b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use jetmoe/jetmoe-8b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jetmoe/jetmoe-8b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jetmoe/jetmoe-8b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/jetmoe/jetmoe-8b
- SGLang
How to use jetmoe/jetmoe-8b 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 "jetmoe/jetmoe-8b" \ --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": "jetmoe/jetmoe-8b", "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 "jetmoe/jetmoe-8b" \ --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": "jetmoe/jetmoe-8b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use jetmoe/jetmoe-8b with Docker Model Runner:
docker model run hf.co/jetmoe/jetmoe-8b
why not include Qwen1.5-MoE-A2.7B in the table?
#4
by J22 - opened
IMHO, Qwen1.5-MoE-A2.7B is SOTA MOE model with 2B active parameters.
Before comparing, it would be good to know how many tokens the model is trained on and what data they used (including the original dense model before upcycling). Furthermore, it should be considered as a concurrent work.