Text Generation
Transformers
Safetensors
English
zeusmm
multimodal
chat
vision
audio
retrieval
text-generation-inference
custom_code
Instructions to use Wonder-Griffin/ZeusMM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wonder-Griffin/ZeusMM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Wonder-Griffin/ZeusMM", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Wonder-Griffin/ZeusMM", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Wonder-Griffin/ZeusMM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Wonder-Griffin/ZeusMM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Wonder-Griffin/ZeusMM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Wonder-Griffin/ZeusMM
- SGLang
How to use Wonder-Griffin/ZeusMM 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 "Wonder-Griffin/ZeusMM" \ --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": "Wonder-Griffin/ZeusMM", "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 "Wonder-Griffin/ZeusMM" \ --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": "Wonder-Griffin/ZeusMM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Wonder-Griffin/ZeusMM with Docker Model Runner:
docker model run hf.co/Wonder-Griffin/ZeusMM
Commit History
-
Update README.md
Verified signaturec2848f3
-
Delete pytorch_model.bin
Verified signaturea20ce4a -
Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (eb52a0c6074392cc60cdc86a8a506add71a383c5) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>c34f5cf -
Re-save weights in safetensors
Verified signaturee1c50d9 -
Re-save weights in safetensors
Verified signature3730acc
-
Create README.md
Verified signaturea1c80de -
Initial ZeusMM: tiny-pretrained weights, tokenizer, config, custom code
Verified signaturefc84ba8 -
Initial ZeusMM: tiny-pretrained weights, tokenizer, config, custom code
Verified signaturec838758 -
initial commit
Verified signature3201870