Transformers
PyTorch
TensorFlow
English
bert
pretraining
multiberts
multiberts-seed_1
multiberts-seed_1-step_20k
Instructions to use google/multiberts-seed_1-step_20k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/multiberts-seed_1-step_20k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("google/multiberts-seed_1-step_20k") model = AutoModelForPreTraining.from_pretrained("google/multiberts-seed_1-step_20k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from google/multiberts-seed_1-step_20k: direct link, hf CLI and curl.
- Browser
- Download file 274 Bytes
-
https://huggingface.co/google/multiberts-seed_1-step_20k/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://google/multiberts-seed_1-step_20k/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/google/multiberts-seed_1-step_20k/resolve/main/tokenizer_config.json
274 Bytes
| {"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "tokenizer_class": "BertTokenizer"} |