Instructions to use ashraq/bert-random-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashraq/bert-random-weights with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ashraq/bert-random-weights")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ashraq/bert-random-weights") model = AutoModelForMaskedLM.from_pretrained("ashraq/bert-random-weights") - Notebooks
- Google Colab
- Kaggle
File size: 398 Bytes
57efab2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"clean_up_tokenization_spaces": true,
"cls_token": "[CLS]",
"do_basic_tokenize": true,
"do_lower_case": false,
"full_tokenizer_file": null,
"mask_token": "[MASK]",
"model_max_length": 512,
"never_split": null,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"strip_accents": null,
"tokenize_chinese_chars": true,
"tokenizer_class": "BertTokenizer",
"unk_token": "[UNK]"
}
|