Instructions to use ishdes/layoutlmv3-ehr-scanned-document-classification-multiclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ishdes/layoutlmv3-ehr-scanned-document-classification-multiclass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ishdes/layoutlmv3-ehr-scanned-document-classification-multiclass")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("ishdes/layoutlmv3-ehr-scanned-document-classification-multiclass") model = AutoModelForSequenceClassification.from_pretrained("ishdes/layoutlmv3-ehr-scanned-document-classification-multiclass", 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 sha256:4ccd6dfd5c00280134b71e99d31faf52a3535f4757172ad6dc59eb0f684e0b65
|
| 3 |
+
size 503731568
|