Image Classification
Transformers
TensorBoard
Safetensors
vit_msn
Generated from Trainer
Eval Results (legacy)
Instructions to use Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10") model = AutoModelForImageClassification.from_pretrained("Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10: direct link, hf CLI and curl.
- Browser
- Download file 806 Bytes
-
https://huggingface.co/Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10/resolve/8d296ad7b25a6b178ec82e65d74680e5294d4bea/config.json
- Command line
-
hf download hf://Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10@8d296ad7b25a6b178ec82e65d74680e5294d4bea/config.json
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curl -L -o config.json https://huggingface.co/Melo1512/vit-msn-small-wbc-classifier-0316-cropped-cleaned-dataset-10/resolve/8d296ad7b25a6b178ec82e65d74680e5294d4bea/config.json
806 Bytes
| { | |
| "_name_or_path": "facebook/vit-msn-small", | |
| "architectures": [ | |
| "ViTMSNForImageClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 384, | |
| "id2label": { | |
| "0": "eosinophils", | |
| "1": "lymphocytes", | |
| "2": "monocytes", | |
| "3": "neutrophils" | |
| }, | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 1536, | |
| "label2id": { | |
| "eosinophils": 0, | |
| "lymphocytes": 1, | |
| "monocytes": 2, | |
| "neutrophils": 3 | |
| }, | |
| "layer_norm_eps": 1e-06, | |
| "model_type": "vit_msn", | |
| "num_attention_heads": 6, | |
| "num_channels": 3, | |
| "num_hidden_layers": 12, | |
| "patch_size": 16, | |
| "problem_type": "single_label_classification", | |
| "qkv_bias": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.44.2" | |
| } | |