Instructions to use nvidia/MambaVision-B-1K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/MambaVision-B-1K with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nvidia/MambaVision-B-1K", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("nvidia/MambaVision-B-1K", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update pipeline tag and add library name
#1
by nielsr HF Staff - opened
This PR updates the pipeline tag to image-classification to accurately reflect the model's primary use case as described in the paper MambaVision: A Hybrid Mamba-Transformer Vision Backbone. It also adds the library_name as transformers since the model is usable with the Hugging Face Transformers library.
ahatamiz changed pull request status to merged