Instructions to use JustFadjrin/batik-vit-model-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JustFadjrin/batik-vit-model-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JustFadjrin/batik-vit-model-classification") 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("JustFadjrin/batik-vit-model-classification") model = AutoModelForImageClassification.from_pretrained("JustFadjrin/batik-vit-model-classification") - Notebooks
- Google Colab
- Kaggle
File size: 1,789 Bytes
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"architectures": [
"ViTForImageClassification"
],
"attention_probs_dropout_prob": 0.0,
"dtype": "float32",
"encoder_stride": 16,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.0,
"hidden_size": 768,
"id2label": {
"0": "Aceh_Pintu_Aceh",
"1": "Bali_Barong",
"2": "Bali_Merak",
"3": "DKI_Ondel_Ondel",
"4": "JawaBarat_Megamendung",
"5": "JawaTimur_Pring",
"6": "Kalimantan_Dayak",
"7": "Lampung_Gajah",
"8": "Madura_Mataketeran",
"9": "Maluku_Pala",
"10": "NTB_Lumbung",
"11": "Papua_Asmat",
"12": "Papua_Cendrawasih",
"13": "Papua_Tifa",
"14": "Solo_Parang",
"15": "SulawesiSelatan_Lontara",
"16": "SumateraBarat_Rumah_Minang",
"17": "SumateraUtara_Boraspati",
"18": "Yogyakarta_Kawung",
"19": "Yogyakarta_Parang"
},
"image_size": 224,
"initializer_range": 0.02,
"intermediate_size": 3072,
"label2id": {
"Aceh_Pintu_Aceh": 0,
"Bali_Barong": 1,
"Bali_Merak": 2,
"DKI_Ondel_Ondel": 3,
"JawaBarat_Megamendung": 4,
"JawaTimur_Pring": 5,
"Kalimantan_Dayak": 6,
"Lampung_Gajah": 7,
"Madura_Mataketeran": 8,
"Maluku_Pala": 9,
"NTB_Lumbung": 10,
"Papua_Asmat": 11,
"Papua_Cendrawasih": 12,
"Papua_Tifa": 13,
"Solo_Parang": 14,
"SulawesiSelatan_Lontara": 15,
"SumateraBarat_Rumah_Minang": 16,
"SumateraUtara_Boraspati": 17,
"Yogyakarta_Kawung": 18,
"Yogyakarta_Parang": 19
},
"layer_norm_eps": 1e-12,
"model_type": "vit",
"num_attention_heads": 12,
"num_channels": 3,
"num_hidden_layers": 12,
"patch_size": 16,
"pooler_act": "tanh",
"pooler_output_size": 768,
"problem_type": "single_label_classification",
"qkv_bias": true,
"transformers_version": "5.0.0",
"use_cache": false
}
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