Instructions to use vikp/text_recognizer_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vikp/text_recognizer_test with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("vikp/text_recognizer_test") model = AutoModel.from_pretrained("vikp/text_recognizer_test") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "text_recognizer/checkpoint-
|
| 3 |
"architectures": [
|
| 4 |
"LangVisionEncoderDecoderModel"
|
| 5 |
],
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "text_recognizer/checkpoint-6000",
|
| 3 |
"architectures": [
|
| 4 |
"LangVisionEncoderDecoderModel"
|
| 5 |
],
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1048833584
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cef6e488d68d7e408eecea5e0cfba52d924631f665ebb050cadea083ec345b3b
|
| 3 |
size 1048833584
|