Instructions to use deepset/gbert-base-germandpr-question_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gbert-base-germandpr-question_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="deepset/gbert-base-germandpr-question_encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deepset/gbert-base-germandpr-question_encoder") model = AutoModel.from_pretrained("deepset/gbert-base-germandpr-question_encoder") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 327 Bytes
e548b7c | 1 | {"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": false, "max_len": 512, "special_tokens_map_file": null, "name_or_path": "deepset/gbert-base", "do_basic_tokenize": true, "never_split": null} |