Instructions to use Nonegom/klue-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nonegom/klue-roberta-large with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Nonegom/klue-roberta-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Nonegom/klue-roberta-large") model = AutoModelForQuestionAnswering.from_pretrained("Nonegom/klue-roberta-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Nonegom/klue-roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 582 Bytes
-
https://huggingface.co/Nonegom/klue-roberta-large/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Nonegom/klue-roberta-large/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Nonegom/klue-roberta-large/resolve/main/tokenizer_config.json
582 Bytes
| {"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "do_basic_tokenize": true, "never_split": null, "bos_token": "[CLS]", "eos_token": "[SEP]", "model_max_length": 512, "tokenizer_class": "BertTokenizer", "special_tokens_map_file": "/opt/ml/.cache/huggingface/transformers/1a24ab4628028ed80dea35ce3334a636dc656fd9a17a09bad377f88f0cbecdac.70c17d6e4d492c8f24f5bb97ab56c7f272e947112c6faf9dd846da42ba13eb23", "name_or_path": "klue/roberta-large"} |