Instructions to use allenai/MolmoWeb-4B-Native with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/MolmoWeb-4B-Native with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="allenai/MolmoWeb-4B-Native")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("allenai/MolmoWeb-4B-Native", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use allenai/MolmoWeb-4B-Native with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "allenai/MolmoWeb-4B-Native" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "allenai/MolmoWeb-4B-Native", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/allenai/MolmoWeb-4B-Native
- SGLang
How to use allenai/MolmoWeb-4B-Native 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/MolmoWeb-4B-Native" \ --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/MolmoWeb-4B-Native", "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/MolmoWeb-4B-Native" \ --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/MolmoWeb-4B-Native", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use allenai/MolmoWeb-4B-Native with Docker Model Runner:
docker model run hf.co/allenai/MolmoWeb-4B-Native
Download model_and_optim/__0_14.distcp from allenai/MolmoWeb-4B-Native: direct link, hf CLI and curl.
- Browser
- Download file 17 MB
-
https://huggingface.co/allenai/MolmoWeb-4B-Native/resolve/main/model_and_optim/__0_14.distcp
- Command line
-
hf download hf://allenai/MolmoWeb-4B-Native/model_and_optim/__0_14.distcp
-
curl -L -o __0_14.distcp https://huggingface.co/allenai/MolmoWeb-4B-Native/resolve/main/model_and_optim/__0_14.distcp
17 MB
- Xet hash:
- 9fd74d0444ab086df236744976041ababab4e335cf87d43aa33f7b21becdc94d
- Size of remote file:
- 17 MB
- SHA256:
- 3e329f90f2763266aee5d14e8af8c349318d4a5499e1063581ab3a7952f94980
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.