Instructions to use TheSleepyJo/mobilevitv2_fold1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheSleepyJo/mobilevitv2_fold1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TheSleepyJo/mobilevitv2_fold1") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("TheSleepyJo/mobilevitv2_fold1") model = AutoModelForImageClassification.from_pretrained("TheSleepyJo/mobilevitv2_fold1") - Notebooks
- Google Colab
- Kaggle
Commit ·
fe6fa7a
1
Parent(s): b588982
Upload MobileViTV2ForImageClassification
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
config.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
"architectures": [
|
| 4 |
"MobileViTV2ForImageClassification"
|
| 5 |
],
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "Thesleepyjo/mobilevitv2_fold1",
|
| 3 |
"architectures": [
|
| 4 |
"MobileViTV2ForImageClassification"
|
| 5 |
],
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 17724225
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:53a116071dabfc6f7dc34ab38a76165ac1920786948547dd2babb563cf2aa89f
|
| 3 |
size 17724225
|