Instructions to use cardiffnlp/bertweet-base-offensive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cardiffnlp/bertweet-base-offensive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cardiffnlp/bertweet-base-offensive")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/bertweet-base-offensive") model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/bertweet-base-offensive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from cardiffnlp/bertweet-base-offensive: direct link, hf CLI and curl.
- Browser
- Download file 318 Bytes
-
https://huggingface.co/cardiffnlp/bertweet-base-offensive/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://cardiffnlp/bertweet-base-offensive/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/cardiffnlp/bertweet-base-offensive/resolve/main/tokenizer_config.json
318 Bytes
| {"normalization": false, "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "do_lower_case": false, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "/home/jupyter/TMP_finetune_tweeteval/model/"} |