Instructions to use dbaranchuk/check with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbaranchuk/check with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dbaranchuk/check") 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("dbaranchuk/check") model = AutoModelForImageClassification.from_pretrained("dbaranchuk/check") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 9085340
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:05dfa6bcde75bdb1f8a2e1b5d2f541b86d6ff4bdf372c699cc03efc9537fcbc5
|
| 3 |
size 9085340
|