Instructions to use PeanutCoding/Layouttest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PeanutCoding/Layouttest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="PeanutCoding/Layouttest")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("PeanutCoding/Layouttest") model = AutoModelForTokenClassification.from_pretrained("PeanutCoding/Layouttest") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1
Browse files
logs/events.out.tfevents.1748958507.phi-ThinkPad-T490
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:81881a172baf5e5ae6fb9bf3b507abf7286eb501e63de26e3413ba7153dc8e1b
|
| 3 |
+
size 8153
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 450724324
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8a477845bc6398211fcaa729a42b875dd2e43d5f08ead2067fd95a300ae70660
|
| 3 |
size 450724324
|