Instructions to use morganchen1007/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use morganchen1007/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="morganchen1007/test") 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("morganchen1007/test") model = AutoModelForImageClassification.from_pretrained("morganchen1007/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "microsoft/resnet-50", | |
| "architectures": [ | |
| "ResNetForImageClassification" | |
| ], | |
| "depths": [ | |
| 3, | |
| 4, | |
| 6, | |
| 3 | |
| ], | |
| "downsample_in_first_stage": false, | |
| "embedding_size": 64, | |
| "hidden_act": "relu", | |
| "hidden_sizes": [ | |
| 256, | |
| 512, | |
| 1024, | |
| 2048 | |
| ], | |
| "id2label": { | |
| "0": "content", | |
| "1": "cover", | |
| "2": "doi" | |
| }, | |
| "label2id": { | |
| "content": 0, | |
| "cover": 1, | |
| "doi": 2 | |
| }, | |
| "layer_type": "bottleneck", | |
| "model_type": "resnet", | |
| "num_channels": 3, | |
| "problem_type": "single_label_classification", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.21.1" | |
| } | |