Image Classification
Transformers
Safetensors
English
mobilevit
sft
vision
medical-imaging
brain-tumor
Instructions to use Jesteban247/mobilevit_small-brain_tumor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jesteban247/mobilevit_small-brain_tumor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Jesteban247/mobilevit_small-brain_tumor") 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("Jesteban247/mobilevit_small-brain_tumor") model = AutoModelForImageClassification.from_pretrained("Jesteban247/mobilevit_small-brain_tumor") - Notebooks
- Google Colab
- Kaggle
Upload 4 files
Browse files- .gitattributes +1 -0
- Brain_Tumor.png +3 -0
- config.json +57 -0
- model.safetensors +3 -0
- preprocessor_config.json +18 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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Brain_Tumor.png filter=lfs diff=lfs merge=lfs -text
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Brain_Tumor.png
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Git LFS Details
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config.json
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{
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"architectures": [
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"MobileViTForImageClassification"
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],
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"aspp_dropout_prob": 0.1,
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"aspp_out_channels": 256,
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"atrous_rates": [
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6,
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12,
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18
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],
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"attention_probs_dropout_prob": 0.0,
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"classifier_dropout_prob": 0.1,
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"conv_kernel_size": 3,
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"dtype": "float32",
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"expand_ratio": 4.0,
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"hidden_act": "silu",
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"hidden_dropout_prob": 0.1,
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"hidden_sizes": [
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144,
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192,
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240
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],
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"id2label": {
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"0": "glioma",
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"1": "meningioma",
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"2": "no_tumor",
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"3": "pituitary"
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},
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"image_size": 256,
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"initializer_range": 0.02,
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"label2id": {
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"glioma": 0,
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"meningioma": 1,
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"no_tumor": 2,
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"pituitary": 3
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},
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"layer_norm_eps": 1e-05,
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"mlp_ratio": 2.0,
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"model_type": "mobilevit",
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"neck_hidden_sizes": [
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16,
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32,
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64,
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96,
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128,
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],
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"num_attention_heads": 4,
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"num_channels": 3,
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"output_stride": 32,
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"patch_size": 2,
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"qkv_bias": true,
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"semantic_loss_ignore_index": 255,
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"transformers_version": "4.56.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:bf033529068238d05565e0ec47d853b6829bd79a6ba306229c3e91d975e74890
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size 19856696
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preprocessor_config.json
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{
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"crop_size": {
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"height": 256,
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"width": 256
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},
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"do_center_crop": true,
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"do_flip_channel_order": true,
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"do_flip_channels": true,
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"do_reduce_labels": false,
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"do_rescale": true,
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"do_resize": true,
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"image_processor_type": "MobileViTImageProcessor",
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 288
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}
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}
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