Instructions to use Adf/test-model-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adf/test-model-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Adf/test-model-v3") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("Adf/test-model-v3") model = AutoModelForZeroShotImageClassification.from_pretrained("Adf/test-model-v3") - Notebooks
- Google Colab
- Kaggle
Upload processor
Browse files- .gitattributes +1 -0
- processor_config.json +31 -0
- tokenizer.json +3 -0
- tokenizer_config.json +24 -0
.gitattributes
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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processor_config.json
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{
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"image_processor": {
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"crop_size": {
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"height": 378,
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"width": 378
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},
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"do_center_crop": true,
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_processor_type": "CLIPImageProcessor",
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 378,
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"width": 378
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}
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},
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"processor_class": "CLIPProcessor"
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:3ef2cc8deb9e37805d5e5393ad945ab60a30963516f8adebfd495629a94176b5
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size 61333815
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tokenizer_config.json
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{
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"add_prefix_space": true,
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"backend": "tokenizers",
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"bos_token": "<s>",
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"clean_up_tokenization_spaces": false,
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"cls_token": "<s>",
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"eos_token": "</s>",
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"is_local": false,
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"local_files_only": false,
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"mask_token": "<mask>",
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"max_length": 77,
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"model_max_length": 1000000000000000019884624838656,
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"pad_to_multiple_of": null,
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"pad_token": "<pad>",
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"pad_token_type_id": 0,
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"padding_side": "right",
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"processor_class": "CLIPProcessor",
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"sep_token": "</s>",
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"stride": 0,
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"tokenizer_class": "XLMRobertaTokenizer",
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"truncation_side": "right",
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"truncation_strategy": "longest_first",
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"unk_token": "<unk>"
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}
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