Instructions to use chanc031965/Tesla_Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chanc031965/Tesla_Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="chanc031965/Tesla_Detection") 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("chanc031965/Tesla_Detection") model = AutoModelForImageClassification.from_pretrained("chanc031965/Tesla_Detection") - Notebooks
- Google Colab
- Kaggle
v2: updated tokenizer
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 343223968
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:37a3267222140dd81a9ea20940cae9c8315689370255e9cce9e37b39a9cc310b
|
| 3 |
size 343223968
|