Instructions to use melll-uff/pt-br_diffcse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use melll-uff/pt-br_diffcse with Transformers:
# Load model directly from transformers import AutoTokenizer, BertForCL tokenizer = AutoTokenizer.from_pretrained("melll-uff/pt-br_diffcse") model = BertForCL.from_pretrained("melll-uff/pt-br_diffcse", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_lower_case": false, | |
| "unk_token": "[UNK]", | |
| "sep_token": "[SEP]", | |
| "pad_token": "[PAD]", | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "tokenize_chinese_chars": true, | |
| "strip_accents": null, | |
| "special_tokens_map_file": "/home/user/.cache/huggingface/transformers/eecc45187d085a1169eed91017d358cc0e9cbdd5dc236bcd710059dbf0a2f816.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", | |
| "name_or_path": "neuralmind/bert-base-portuguese-cased", | |
| "do_basic_tokenize": true, | |
| "never_split": null, | |
| "model_max_length": 512 | |
| } |