Instructions to use FrinzTheCoder/bert-base-multilingual-cased-orm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FrinzTheCoder/bert-base-multilingual-cased-orm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FrinzTheCoder/bert-base-multilingual-cased-orm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FrinzTheCoder/bert-base-multilingual-cased-orm") model = AutoModelForSequenceClassification.from_pretrained("FrinzTheCoder/bert-base-multilingual-cased-orm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from FrinzTheCoder/bert-base-multilingual-cased-orm: direct link, hf CLI and curl.
- Browser
- Download file 125 Bytes
-
https://huggingface.co/FrinzTheCoder/bert-base-multilingual-cased-orm/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://FrinzTheCoder/bert-base-multilingual-cased-orm/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/FrinzTheCoder/bert-base-multilingual-cased-orm/resolve/main/special_tokens_map.json
125 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |