Instructions to use jlee-larr/dynaflip-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jlee-larr/dynaflip-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="jlee-larr/dynaflip-base", trust_remote_code=True) pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jlee-larr/dynaflip-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add link to paper, usage code snippet and pipeline tag
#1
by nielsr HF Staff - opened
This PR improves the model card's metadata and adds a link to https://huggingface.co/papers/2605.30350.
Thanks for the improvements! Merging now.
jlee-larr changed pull request status to merged