Instructions to use pphildan/vit-base-patch16-224-v21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pphildan/vit-base-patch16-224-v21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pphildan/vit-base-patch16-224-v21") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("pphildan/vit-base-patch16-224-v21") model = AutoModelForImageClassification.from_pretrained("pphildan/vit-base-patch16-224-v21") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
runs/May20_07-59-22_9726b5ef393e/events.out.tfevents.1684569574.9726b5ef393e.1802.4
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4b7412c06bb43a2a8e9275010d996390d5374d536392f2c24e7b54a0d85f1504
|
| 3 |
+
size 31168
|