Instructions to use sarabi1005/vit-base-beans_50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sarabi1005/vit-base-beans_50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sarabi1005/vit-base-beans_50") 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("sarabi1005/vit-base-beans_50") model = AutoModelForImageClassification.from_pretrained("sarabi1005/vit-base-beans_50", device_map="auto") - 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:a041aec98dc7f8bb03790d3d359f2ef1668d71360f05a81d5e55d0e983ea301e
|
| 3 |
+
size 343223968
|