Instructions to use dybdyb/mobilevit-houseplants with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dybdyb/mobilevit-houseplants with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dybdyb/mobilevit-houseplants") 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("dybdyb/mobilevit-houseplants") model = AutoModelForImageClassification.from_pretrained("dybdyb/mobilevit-houseplants", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- onnx/model.onnx +3 -0
- onnx/model_quantized.onnx +3 -0
onnx/model.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:82f49b6cbf45d8b3a009c31c8eb5cbedcc9a76380179177563f790a71cf93272
|
| 3 |
+
size 20136099
|
onnx/model_quantized.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a3dd0603874cf8c95c2d3a8b1dd050ae2f01d3d23c87cac56d87c7b59fccc90e
|
| 3 |
+
size 5603334
|