Question Answering
Transformers
PyTorch
Safetensors
English
deberta-v2
deberta
deberta-v3
deberta-v3-large
Eval Results (legacy)
Instructions to use deepset/deberta-v3-large-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/deberta-v3-large-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="deepset/deberta-v3-large-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/deberta-v3-large-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/deberta-v3-large-squad2") - Inference
- Notebooks
- Google Colab
- Kaggle
Sebastian commited on
Commit 路
5b66c60
1
Parent(s): cf83ca2
Adding model_max_length to the tokenizer config
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
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{"do_lower_case": false, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "split_by_punct": false, "vocab_type": "spm", "special_tokens_map_file": null, "name_or_path": "checkpoint_deberta_large", "sp_model_kwargs": {}, "tokenizer_class": "DebertaV2Tokenizer"}
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{"do_lower_case": false, "model_max_length": 512, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "split_by_punct": false, "vocab_type": "spm", "special_tokens_map_file": null, "name_or_path": "checkpoint_deberta_large", "sp_model_kwargs": {}, "tokenizer_class": "DebertaV2Tokenizer"}
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