Instructions to use Prot10/swin-tiny-patch4-window7-224-for-pre_evaluation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prot10/swin-tiny-patch4-window7-224-for-pre_evaluation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Prot10/swin-tiny-patch4-window7-224-for-pre_evaluation") 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("Prot10/swin-tiny-patch4-window7-224-for-pre_evaluation") model = AutoModelForImageClassification.from_pretrained("Prot10/swin-tiny-patch4-window7-224-for-pre_evaluation") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5a026f007fa96069dca7e33d7b91ec13bf9e1c6e434cf03f292c65d83b0bcfd4
|
| 3 |
+
size 110352060
|