Instructions to use Dewa/Dog_Model_From_Scratch_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dewa/Dog_Model_From_Scratch_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Dewa/Dog_Model_From_Scratch_v2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import ClassificationModelForDogEmotion model = ClassificationModelForDogEmotion.from_pretrained("Dewa/Dog_Model_From_Scratch_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "ClassificationModelForDogEmotion" | |
| ], | |
| "dropout": 0.3, | |
| "hidden_layer1": 512, | |
| "hidden_layer2": 128, | |
| "input_dim": 3, | |
| "model_type": "simple_image_classification", | |
| "output_dim": 4, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.31.0" | |
| } | |