Instructions to use arvisioncode/lilt_mt_re_all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arvisioncode/lilt_mt_re_all with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import LiLTRobertaLikeForRelationExtraction model = LiLTRobertaLikeForRelationExtraction.from_pretrained("arvisioncode/lilt_mt_re_all", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from arvisioncode/lilt_mt_re_all: direct link, hf CLI and curl.
- Browser
- Download file 356 Bytes
-
https://huggingface.co/arvisioncode/lilt_mt_re_all/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://arvisioncode/lilt_mt_re_all/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/arvisioncode/lilt_mt_re_all/resolve/main/tokenizer_config.json
356 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"}, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "xlm-roberta-base"} |