Instructions to use rudrankriyam/Janus-Pro-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rudrankriyam/Janus-Pro-1B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import MultiModalityCausalLM model = MultiModalityCausalLM.from_pretrained("rudrankriyam/Janus-Pro-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rudrankriyam/Janus-Pro-1B: direct link, hf CLI and curl.
- Browser
- Download file 4.18 GB
-
https://huggingface.co/rudrankriyam/Janus-Pro-1B/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rudrankriyam/Janus-Pro-1B/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rudrankriyam/Janus-Pro-1B/resolve/main/pytorch_model.bin
4.18 GB
- Xet hash:
- c1ffc28cc8bca08918829f98603f31c8ff7b80d81947de88028d0be238d04440
- Size of remote file:
- 4.18 GB
- SHA256:
- ea7cf164cbed272be2a9999bc4c314da6a6f23ef51871ddef3afc2c0c430cc3f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.