Instructions to use datalab-to/inline_math_det0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datalab-to/inline_math_det0 with Transformers:
# Load model directly from transformers import EfficientViTForSemanticSegmentation model = EfficientViTForSemanticSegmentation.from_pretrained("datalab-to/inline_math_det0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload EfficientViTForSemanticSegmentation
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "/home/ubuntu/models/inline-math0/checkpoint-
|
| 3 |
"architectures": [
|
| 4 |
"EfficientViTForSemanticSegmentation"
|
| 5 |
],
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "/home/ubuntu/models/inline-math0/checkpoint-31248",
|
| 3 |
"architectures": [
|
| 4 |
"EfficientViTForSemanticSegmentation"
|
| 5 |
],
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 153825684
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e85c39b15f04ef2696c6fd4fc7636715bd2cdcfdee8f826694710cf055b753f8
|
| 3 |
size 153825684
|