Instructions to use ghaith1997/layoutmv3-testing-document-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghaith1997/layoutmv3-testing-document-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghaith1997/layoutmv3-testing-document-classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("ghaith1997/layoutmv3-testing-document-classification") model = AutoModelForSequenceClassification.from_pretrained("ghaith1997/layoutmv3-testing-document-classification") - 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:b319def657676b77cf98db35b1d650ec7469195b780cf656aa2e52cd38074e22
|
| 3 |
+
size 503716188
|