Instructions to use peter-yuma/natix-test-model-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peter-yuma/natix-test-model-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="peter-yuma/natix-test-model-2") 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("peter-yuma/natix-test-model-2") model = AutoModelForImageClassification.from_pretrained("peter-yuma/natix-test-model-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model.safetensors
Browse files- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:56a376863c5b2cb7201fe3537625c115bbe163b600185bb62dcd4772f13b6d38
|
| 3 |
+
size 343223968
|