Image Classification
Transformers
Safetensors
mobilevit
knowledge_distillation
vision
Generated from Trainer
Instructions to use c14kevincardenas/mobilevit-x-small_alpha0.7_temp3.0_t3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use c14kevincardenas/mobilevit-x-small_alpha0.7_temp3.0_t3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="c14kevincardenas/mobilevit-x-small_alpha0.7_temp3.0_t3") 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("c14kevincardenas/mobilevit-x-small_alpha0.7_temp3.0_t3") model = AutoModelForImageClassification.from_pretrained("c14kevincardenas/mobilevit-x-small_alpha0.7_temp3.0_t3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "MobileViTForImageClassification" | |
| ], | |
| "aspp_dropout_prob": 0.1, | |
| "aspp_out_channels": 256, | |
| "atrous_rates": [ | |
| 6, | |
| 12, | |
| 18 | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "classifier_dropout_prob": 0.1, | |
| "conv_kernel_size": 3, | |
| "expand_ratio": 4.0, | |
| "hidden_act": "silu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_sizes": [ | |
| 96, | |
| 120, | |
| 144 | |
| ], | |
| "layer_norm_eps": 1e-05, | |
| "mlp_ratio": 2.0, | |
| "model_type": "mobilevit", | |
| "neck_hidden_sizes": [ | |
| 16, | |
| 32, | |
| 48, | |
| 64, | |
| 80, | |
| 96, | |
| 384 | |
| ], | |
| "num_attention_heads": 4, | |
| "num_channels": 3, | |
| "output_stride": 32, | |
| "patch_size": 2, | |
| "qkv_bias": true, | |
| "semantic_loss_ignore_index": 255, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.20.0.dev0" | |
| } |