Text Generation
Transformers
Safetensors
English
Korean
Motif
feature-extraction
motif
motif-3
mixture-of-experts
Mixture of Experts
long-context
multilingual
preview
conversational
custom_code
Instructions to use Motif-Technologies/Motif-3-Beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Motif-Technologies/Motif-3-Beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Motif-Technologies/Motif-3-Beta", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Motif-Technologies/Motif-3-Beta", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Motif-Technologies/Motif-3-Beta with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Motif-Technologies/Motif-3-Beta" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Motif-Technologies/Motif-3-Beta", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Motif-Technologies/Motif-3-Beta
- SGLang
How to use Motif-Technologies/Motif-3-Beta 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 "Motif-Technologies/Motif-3-Beta" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Motif-Technologies/Motif-3-Beta", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "Motif-Technologies/Motif-3-Beta" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Motif-Technologies/Motif-3-Beta", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Motif-Technologies/Motif-3-Beta with Docker Model Runner:
docker model run hf.co/Motif-Technologies/Motif-3-Beta
This looks absolutely amazing.
#5
by aperso - opened
Ngl, I didn't expect anything great to come out of the 국산 AI race, but this is just amazing.
An actually novel architecture using an extremely promising custom attention.
One of if not the first major model to employ DeepSeek mHC, which is less than half a year old.
The future may be bright for our country. Very well done.