Instructions to use ArwaAbdul/swinv2-tiny-patch4-window8-datasetinriching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArwaAbdul/swinv2-tiny-patch4-window8-datasetinriching with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ArwaAbdul/swinv2-tiny-patch4-window8-datasetinriching") 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("ArwaAbdul/swinv2-tiny-patch4-window8-datasetinriching") model = AutoModelForImageClassification.from_pretrained("ArwaAbdul/swinv2-tiny-patch4-window8-datasetinriching") - 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 sha256:5c2058eabb246679230caa5786d188d72fbb68e416108e0fbcac1363886d6f8d
|
| 3 |
+
size 110356296
|