Image Classification
Transformers
TensorBoard
Safetensors
dinov2
Generated from Trainer
Eval Results (legacy)
Instructions to use LuGot16/spermatogenesis-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LuGot16/spermatogenesis-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="LuGot16/spermatogenesis-classifier") 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("LuGot16/spermatogenesis-classifier") model = AutoModelForImageClassification.from_pretrained("LuGot16/spermatogenesis-classifier") - Notebooks
- Google Colab
- Kaggle
File size: 1,149 Bytes
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"apply_layernorm": true,
"architectures": [
"Dinov2ForImageClassification"
],
"attention_probs_dropout_prob": 0.0,
"drop_path_rate": 0.0,
"dtype": "float32",
"hidden_act": "gelu",
"hidden_dropout_prob": 0.0,
"hidden_size": 768,
"id2label": {
"0": "I-IV",
"1": "IX-X",
"2": "V-VI",
"3": "VII-VII",
"4": "XI- XII"
},
"image_size": 518,
"initializer_range": 0.02,
"label2id": {
"I-IV": 0,
"IX-X": 1,
"V-VI": 2,
"VII-VII": 3,
"XI- XII": 4
},
"layer_norm_eps": 1e-06,
"layerscale_value": 1.0,
"mlp_ratio": 4,
"model_type": "dinov2",
"num_attention_heads": 12,
"num_channels": 3,
"num_hidden_layers": 12,
"out_features": [
"stage12"
],
"out_indices": [
12
],
"patch_size": 14,
"qkv_bias": true,
"reshape_hidden_states": true,
"stage_names": [
"stem",
"stage1",
"stage2",
"stage3",
"stage4",
"stage5",
"stage6",
"stage7",
"stage8",
"stage9",
"stage10",
"stage11",
"stage12"
],
"transformers_version": "5.6.2",
"use_cache": false,
"use_mask_token": true,
"use_swiglu_ffn": false
}
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