Instructions to use HungNguyen142/layoutlm-mcocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HungNguyen142/layoutlm-mcocr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="HungNguyen142/layoutlm-mcocr")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("HungNguyen142/layoutlm-mcocr") model = AutoModelForTokenClassification.from_pretrained("HungNguyen142/layoutlm-mcocr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 11
Browse files
logs/events.out.tfevents.1733253804.63d9064179a3.23.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2e626ad53ae9d7ea830dc32605c3626f087f772979a05d9f5dbcc28bb063ae7c
|
| 3 |
+
size 12902
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 450548984
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3c1133f0c1fb4b62414612af0743757420414598493daa450d58416713347c42
|
| 3 |
size 450548984
|