Instructions to use Dhineshk/TestDocumentQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dhineshk/TestDocumentQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="Dhineshk/TestDocumentQuestionAnswering")# Load model directly from transformers import AutoProcessor, AutoModelForDocumentQuestionAnswering processor = AutoProcessor.from_pretrained("Dhineshk/TestDocumentQuestionAnswering") model = AutoModelForDocumentQuestionAnswering.from_pretrained("Dhineshk/TestDocumentQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2600
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 802204017
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0e77f6772479a8c39289b3f3a75b20b640ec98b44804e767646940c311b7cc0a
|
| 3 |
size 802204017
|