Instructions to use facebook/metaclip-b16-400m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/metaclip-b16-400m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="facebook/metaclip-b16-400m") 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("facebook/metaclip-b16-400m") model = AutoModelForZeroShotImageClassification.from_pretrained("facebook/metaclip-b16-400m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
df47ad2
1
Parent(s): 58148bb
Upload metaclip_b16_400m.bin
Browse files- metaclip_b16_400m.bin +3 -0
metaclip_b16_400m.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a1a6eeedfbae970ba5cc56adf99c58fd1c05b3cba222a9a392f196bd54cb36c6
|
| 3 |
+
size 598599478
|