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
| { | |
| "_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 | |
| } |