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mattdangerwmattdangerw
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Reduce the metadata we track per presets (#1991)
We can grab the class name from the keras.io, and we don't need to add a model card anymore, given that our kaggle pages are now linked and act as a much better model card.
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‎keras_hub/src/models/albert/albert_presets.py‎

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"Trained on English Wikipedia + BooksCorpus."
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),
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"params": 11683584,
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"official_name": "ALBERT",
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"path": "albert",
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"model_card": "https://github.com/google-research/albert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/albert/keras/albert_base_en_uncased/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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),
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"params": 17683968,
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"official_name": "ALBERT",
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"path": "albert",
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"model_card": "https://github.com/google-research/albert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/albert/keras/albert_large_en_uncased/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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),
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"params": 58724864,
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"official_name": "ALBERT",
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"path": "albert",
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"model_card": "https://github.com/google-research/albert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/albert/keras/albert_extra_large_en_uncased/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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),
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"params": 222595584,
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"official_name": "ALBERT",
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"path": "albert",
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"model_card": "https://github.com/google-research/albert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/albert/keras/albert_extra_extra_large_en_uncased/2",
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},

‎keras_hub/src/models/bart/bart_presets.py‎

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"Trained on BookCorpus, English Wikipedia and CommonCrawl."
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"params": 139417344,
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"official_name": "BART",
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"path": "bart",
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"model_card": "https://github.com/facebookresearch/fairseq/blob/main/examples/bart/README.md",
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},
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"kaggle_handle": "kaggle://keras/bart/keras/bart_base_en/2",
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},
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"Trained on BookCorpus, English Wikipedia and CommonCrawl."
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),
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"params": 406287360,
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"official_name": "BART",
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"path": "bart",
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"model_card": "https://github.com/facebookresearch/fairseq/blob/main/examples/bart/README.md",
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},
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"config": {
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"vocabulary_size": 50265,
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"summarization dataset."
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),
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"params": 406287360,
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"official_name": "BART",
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"path": "bart",
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"model_card": "https://github.com/facebookresearch/fairseq/blob/main/examples/bart/README.md",
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},
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"config": {
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"vocabulary_size": 50264,

‎keras_hub/src/models/bert/bert_presets.py‎

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"Trained on English Wikipedia + BooksCorpus."
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"params": 4385920,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_tiny_en_uncased/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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),
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"params": 28763648,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_small_en_uncased/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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"params": 41373184,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_medium_en_uncased/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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),
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"params": 109482240,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_base_en_uncased/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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"params": 108310272,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_base_en/2",
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},
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"12-layer BERT model. Trained on Chinese Wikipedia."
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"params": 102267648,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_base_zh/2",
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},
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"12-layer BERT model where case is maintained. Trained on trained on Wikipedias of 104 languages"
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"params": 177853440,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_base_multi/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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"params": 335141888,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_large_en_uncased/2",
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},
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"Trained on English Wikipedia + BooksCorpus."
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"params": 333579264,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_large_en/2",
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},
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"The bert_tiny_en_uncased backbone model fine-tuned on the SST-2 sentiment analysis dataset."
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),
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"params": 4385920,
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"official_name": "BERT",
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"path": "bert",
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"model_card": "https://github.com/google-research/bert/blob/master/README.md",
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},
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"kaggle_handle": "kaggle://keras/bert/keras/bert_tiny_en_uncased_sst2/4",
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},

‎keras_hub/src/models/bloom/bloom_presets.py‎

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"trained on 45 natural languages and 12 programming languages."
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"params": 559214592,
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"official_name": "BLOOM",
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"path": "bloom",
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"model_card": "https://huggingface.co/bigscience/bloom-560m",
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},
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"kaggle_handle": "kaggle://keras/bloom/keras/bloom_560m_multi/3",
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},
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"trained on 45 natural languages and 12 programming languages."
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"params": 1065314304,
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"official_name": "BLOOM",
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"path": "bloom",
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"model_card": "https://huggingface.co/bigscience/bloom-1b1",
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},
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"kaggle_handle": "kaggle://keras/bloom/keras/bloom_1.1b_multi/1",
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},
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"trained on 45 natural languages and 12 programming languages."
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"params": 1722408960,
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"official_name": "BLOOM",
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"path": "bloom",
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"model_card": "https://huggingface.co/bigscience/bloom-1b7",
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},
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"kaggle_handle": "kaggle://keras/bloom/keras/bloom_1.7b_multi/1",
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},
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"trained on 45 natural languages and 12 programming languages."
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"params": 3002557440,
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"official_name": "BLOOM",
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"path": "bloom",
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"model_card": "https://huggingface.co/bigscience/bloom-3b",
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},
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"kaggle_handle": "kaggle://keras/bloom/keras/bloom_3b_multi/1",
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"finetuned on crosslingual task mixture (xP3) dataset."
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"params": 559214592,
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"official_name": "BLOOMZ",
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"path": "bloom",
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"model_card": "https://huggingface.co/bigscience/bloomz-560m",
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},
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"kaggle_handle": "kaggle://keras/bloom/keras/bloomz_560m_multi/1",
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},
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"finetuned on crosslingual task mixture (xP3) dataset."
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"params": 1065314304,
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"official_name": "BLOOMZ",
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"path": "bloom",
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"model_card": "https://huggingface.co/bigscience/bloomz-1b1",
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},
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"kaggle_handle": "kaggle://keras/bloom/keras/bloomz_1.1b_multi/1",
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"finetuned on crosslingual task mixture (xP3) dataset."
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"params": 1722408960,
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"official_name": "BLOOMZ",
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"path": "bloom",
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"model_card": "https://huggingface.co/bigscience/bloomz-1b7",
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},
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"kaggle_handle": "kaggle://keras/bloom/keras/bloomz_1.7b_multi/1",
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},
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"finetuned on crosslingual task mixture (xP3) dataset."
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"params": 3002557440,
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"official_name": "BLOOMZ",
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"path": "bloom",
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"model_card": "https://huggingface.co/bigscience/bloomz-3b",
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},
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"kaggle_handle": "kaggle://keras/bloom/keras/bloomz_3b_multi/1",
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},

‎keras_hub/src/models/clip/clip_presets.py‎

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"text, patch size of 16, CLIP model."
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"params": 149620934,
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"official_name": "CLIP",
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"path": "clip",
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"model_card": "https://github.com/openai/CLIP/blob/main/model-card.md",
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},
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"kaggle_handle": "kaggle://keras/clip/keras/clip_vit_base_patch16/1",
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},
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"text, patch size of 32, CLIP model."
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"params": 151277363,
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"official_name": "CLIP",
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"path": "clip",
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"model_card": "https://github.com/openai/CLIP/blob/main/model-card.md",
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},
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"kaggle_handle": "kaggle://keras/clip/keras/clip_vit_base_patch32/1",
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"text, patch size of 14, CLIP model."
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"params": 427616770,
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"official_name": "CLIP",
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"path": "clip",
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"model_card": "https://github.com/openai/CLIP/blob/main/model-card.md",
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},
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"kaggle_handle": "kaggle://keras/clip/keras/clip_vit_large_patch14/1",
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},
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"text, patch size of 14, image size of 336, CLIP model."
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"params": 427944770,
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"official_name": "CLIP",
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"path": "clip",
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"model_card": "https://github.com/openai/CLIP/blob/main/model-card.md",
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},
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"kaggle_handle": "kaggle://keras/clip/keras/clip_vit_large_patch14_336/1",
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},
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"text, patch size of 32, Open CLIP model."
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"params": 151277363,
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"official_name": "Open CLIP",
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"path": "clip",
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"model_card": "https://github.com/mlfoundations/open_clip",
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},
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"kaggle_handle": "kaggle://keras/clip/keras/clip_vit_b_32_laion2b_s34b_b79k/1",
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"text, patch size of 14, Open CLIP model."
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"params": 986109698,
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"official_name": "Open CLIP",
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"path": "clip",
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"model_card": "https://github.com/mlfoundations/open_clip",
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},
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"kaggle_handle": "kaggle://keras/clip/keras/clip_vit_h_14_laion2b_s32b_b79k/1",
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},
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"text, patch size of 14, Open CLIP model."
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"params": 1366678530,
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"official_name": "Open CLIP",
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"path": "clip",
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"model_card": "https://github.com/mlfoundations/open_clip",
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},
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"kaggle_handle": "kaggle://keras/clip/keras/clip_vit_g_14_laion2b_s12b_b42k/1",
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},
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"text, patch size of 14, Open CLIP model."
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"params": 2539567362,
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"official_name": "Open CLIP",
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"path": "clip",
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"model_card": "https://github.com/mlfoundations/open_clip",
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},
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"kaggle_handle": "kaggle://keras/clip/keras/clip_vit_bigg_14_laion2b_39b_b160k/1",
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},

‎keras_hub/src/models/deberta_v3/deberta_v3_presets.py‎

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"Trained on English Wikipedia, BookCorpus and OpenWebText."
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"params": 70682112,
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"official_name": "DeBERTaV3",
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"path": "deberta_v3",
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"model_card": "https://huggingface.co/microsoft/deberta-v3-xsmall",
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},
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"kaggle_handle": "kaggle://keras/deberta_v3/keras/deberta_v3_extra_small_en/2",
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},
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"Trained on English Wikipedia, BookCorpus and OpenWebText."
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"params": 141304320,
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"official_name": "DeBERTaV3",
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"path": "deberta_v3",
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"model_card": "https://huggingface.co/microsoft/deberta-v3-small",
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},
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"kaggle_handle": "kaggle://keras/deberta_v3/keras/deberta_v3_small_en/2",
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},
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"Trained on English Wikipedia, BookCorpus and OpenWebText."
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"params": 183831552,
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"official_name": "DeBERTaV3",
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"path": "deberta_v3",
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"model_card": "https://huggingface.co/microsoft/deberta-v3-base",
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},
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"kaggle_handle": "kaggle://keras/deberta_v3/keras/deberta_v3_base_en/2",
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},
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"Trained on English Wikipedia, BookCorpus and OpenWebText."
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"params": 434012160,
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"official_name": "DeBERTaV3",
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"path": "deberta_v3",
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"model_card": "https://huggingface.co/microsoft/deberta-v3-large",
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},
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"kaggle_handle": "kaggle://keras/deberta_v3/keras/deberta_v3_large_en/2",
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},
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"Trained on the 2.5TB multilingual CC100 dataset."
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"params": 278218752,
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"official_name": "DeBERTaV3",
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"path": "deberta_v3",
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"model_card": "https://huggingface.co/microsoft/mdeberta-v3-base",
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},
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"kaggle_handle": "kaggle://keras/deberta_v3/keras/deberta_v3_base_multi/2",
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},

‎keras_hub/src/models/deeplab_v3/deeplab_v3_presets.py‎

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"which is having categorical accuracy of 90.01 and 0.63 Mean IoU."
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"params": 39190656,
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"official_name": "DeepLabV3",
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"path": "deeplab_v3",
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"model_card": "https://arxiv.org/abs/1802.02611",
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},
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"kaggle_handle": "kaggle://keras/deeplabv3plus/keras/deeplab_v3_plus_resnet50_pascalvoc/3",
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},

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