Instructions to use hf-internal-testing/tiny-random-layoutlmv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-layoutlmv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-layoutlmv3")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-layoutlmv3") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-layoutlmv3") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
config.json
CHANGED
|
@@ -36,5 +36,5 @@
|
|
| 36 |
"transformers_version": "4.22.0.dev0",
|
| 37 |
"type_vocab_size": 1,
|
| 38 |
"visual_embed": true,
|
| 39 |
-
"vocab_size":
|
| 40 |
}
|
|
|
|
| 36 |
"transformers_version": "4.22.0.dev0",
|
| 37 |
"type_vocab_size": 1,
|
| 38 |
"visual_embed": true,
|
| 39 |
+
"vocab_size": 50265
|
| 40 |
}
|
pytorch_model.bin
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 sha256:6339e4e419a27b193fe3a914fbb4cbca579911a27ca02b4d02fdca3de8b8cc9f
|
| 3 |
+
size 4101559
|