Instructions to use cringgaard/extrapolation_length with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cringgaard/extrapolation_length with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="cringgaard/extrapolation_length") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("cringgaard/extrapolation_length") model = AutoModelForZeroShotImageClassification.from_pretrained("cringgaard/extrapolation_length") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
8e5b58a | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:6764f0d33c9489179f4bc48d6ef233bedab0dc4cdcb912b54138745d0b22701c
size 1710537716
|