Image Feature Extraction
Transformers
Safetensors
dinov2
dino
vision
image-embeddings
pet-recognition
Instructions to use bcd8697/trial-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bcd8697/trial-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="bcd8697/trial-model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("bcd8697/trial-model") model = AutoModel.from_pretrained("bcd8697/trial-model") - Notebooks
- Google Colab
- Kaggle
Upload DINO-v2-small-for-animal-identification.zip
Browse files
DINO-v2-small-for-animal-identification.zip
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5b13108cf8cc440be6b5c19fd0f517b2f8705a80430c644a7d461b1ed8662fb5
|
| 3 |
+
size 164056095
|