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
File size: 282 Bytes
9809214 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"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"
}
|