Instructions to use hf-tiny-model-private/tiny-random-RemBertForMultipleChoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RemBertForMultipleChoice with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForMultipleChoice") model = AutoModelForMultipleChoice.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForMultipleChoice") - Notebooks
- Google Colab
- Kaggle
File size: 522 Bytes
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"bos_token": "[CLS]",
"clean_up_tokenization_spaces": true,
"cls_token": "[CLS]",
"do_lower_case": false,
"eos_token": "[SEP]",
"keep_accents": true,
"mask_token": "[MASK]",
"model_max_length": 512,
"pad_token": "[PAD]",
"remove_space": true,
"sep_token": "[SEP]",
"special_tokens_map_file": "/home/runner/.cache/huggingface/hub/models--google--rembert/snapshots/65da5133da36e29dfca67d4f0dd9f7f9db21b563/special_tokens_map.json",
"tokenizer_class": "RemBertTokenizer",
"unk_token": "[UNK]"
}
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