Instructions to use Twitter/twhin-bert-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Twitter/twhin-bert-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Twitter/twhin-bert-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Twitter/twhin-bert-large") model = AutoModelForMaskedLM.from_pretrained("Twitter/twhin-bert-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Twitter/twhin-bert-large: direct link, hf CLI and curl.
- Browser
- Download file 373 Bytes
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https://huggingface.co/Twitter/twhin-bert-large/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Twitter/twhin-bert-large/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/Twitter/twhin-bert-large/resolve/main/tokenizer_config.json
373 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "name_or_path": "./con-large-308k", "special_tokens_map_file": null, "tokenizer_class": "XLMRobertaTokenizer"} |