Instructions to use ericxlima/DogsClassifierModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ericxlima/DogsClassifierModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ericxlima/DogsClassifierModel") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("ericxlima/DogsClassifierModel") model = AutoModel.from_pretrained("ericxlima/DogsClassifierModel") - Notebooks
- Google Colab
- Kaggle
File size: 344 Bytes
a991b86 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"_class_name": "DDIMScheduler",
"_diffusers_version": "0.8.0",
"beta_end": 0.012,
"beta_schedule": "scaled_linear",
"beta_start": 0.00085,
"clip_sample": false,
"num_train_timesteps": 1000,
"prediction_type": "v_prediction",
"set_alpha_to_one": false,
"skip_prk_steps": true,
"steps_offset": 1,
"trained_betas": null
} |