Image-Text-to-Text
Transformers
PyTorch
English
molmo
text-generation
multimodal
Mixture of Experts
olmo
olmoe
molmoe
custom_code
Instructions to use allenai/MolmoE-1B-0924 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/MolmoE-1B-0924 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="allenai/MolmoE-1B-0924", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("allenai/MolmoE-1B-0924", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use allenai/MolmoE-1B-0924 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "allenai/MolmoE-1B-0924" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "allenai/MolmoE-1B-0924", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/allenai/MolmoE-1B-0924
- SGLang
How to use allenai/MolmoE-1B-0924 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 "allenai/MolmoE-1B-0924" \ --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": "allenai/MolmoE-1B-0924", "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 "allenai/MolmoE-1B-0924" \ --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": "allenai/MolmoE-1B-0924", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use allenai/MolmoE-1B-0924 with Docker Model Runner:
docker model run hf.co/allenai/MolmoE-1B-0924
VRAM - how to run
#6
by SinanAkkoyun - opened
How do you run inference with your API?
May I ask what quantization your demo inference runs at?
This is an unquantized model. You can estimate the total expected VRAM required by adding the size of each checkpoint file.
To run this on a 24GB GPU, you can try this env var or the 4-bit per weight quantized model I linked in the last comment here: https://huggingface.co/allenai/MolmoE-1B-0924/discussions/4