Instructions to use frgfm/resnet34 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use frgfm/resnet34 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="frgfm/resnet34") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("frgfm/resnet34", dtype="auto") - Notebooks
- Google Colab
- Kaggle
fg-mindee commited on
Commit ·
5bf6529
1
Parent(s): 8da6288
feat: Added ONNX model
Browse files- README.md +1 -0
- model.onnx +3 -0
README.md
CHANGED
|
@@ -3,6 +3,7 @@ license: apache-2.0
|
|
| 3 |
tags:
|
| 4 |
- image-classification
|
| 5 |
- pytorch
|
|
|
|
| 6 |
datasets:
|
| 7 |
- imagenette
|
| 8 |
---
|
|
|
|
| 3 |
tags:
|
| 4 |
- image-classification
|
| 5 |
- pytorch
|
| 6 |
+
- onnx
|
| 7 |
datasets:
|
| 8 |
- imagenette
|
| 9 |
---
|
model.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5f52a57096dd25d012064abaa54ce8bfea84b9b97da90e160c2f5914d03b71ee
|
| 3 |
+
size 85133269
|