Instructions to use TGrote11/Math_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TGrote11/Math_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="TGrote11/Math_Classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import CNN model = CNN.from_pretrained("TGrote11/Math_Classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- .ipynb_checkpoints/config-checkpoint.json +8 -0
- config.json +8 -0
- pytorch_model.bin +3 -0
.ipynb_checkpoints/config-checkpoint.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"CNN"
|
| 4 |
+
],
|
| 5 |
+
"model_type": "cnn",
|
| 6 |
+
"torch_dtype": "float32",
|
| 7 |
+
"transformers_version": "4.17.0"
|
| 8 |
+
}
|
config.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"CNN"
|
| 4 |
+
],
|
| 5 |
+
"model_type": "cnn",
|
| 6 |
+
"torch_dtype": "float32",
|
| 7 |
+
"transformers_version": "4.17.0"
|
| 8 |
+
}
|
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d439b9ca0fa069596da0bcf5e5a2d43126f579e0528f767f0e20be493a01abd2
|
| 3 |
+
size 29161837
|