Instructions to use FKTech/roberta-large-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FKTech/roberta-large-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FKTech/roberta-large-rte")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FKTech/roberta-large-rte") model = AutoModelForSequenceClassification.from_pretrained("FKTech/roberta-large-rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from FKTech/roberta-large-rte: direct link, hf CLI and curl.
- Browser
- Download file 388 Bytes
-
https://huggingface.co/FKTech/roberta-large-rte/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://FKTech/roberta-large-rte/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/FKTech/roberta-large-rte/resolve/main/tokenizer_config.json
388 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "RobertaTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": "<unk>" | |
| } | |