Instructions to use ModelTC/bart-base-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-squad 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="ModelTC/bart-base-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-squad") model = AutoModelForQuestionAnswering.from_pretrained("ModelTC/bart-base-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from ModelTC/bart-base-squad: direct link, hf CLI and curl.
- Browser
- Download file 374 Bytes
-
https://huggingface.co/ModelTC/bart-base-squad/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ModelTC/bart-base-squad/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ModelTC/bart-base-squad/resolve/main/tokenizer_config.json
374 Bytes
| {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "add_prefix_space": false, "errors": "replace", "sep_token": "</s>", "cls_token": "<s>", "pad_token": "<pad>", "mask_token": "<mask>", "trim_offsets": true, "use_fase": true, "special_tokens_map_file": null, "name_or_path": "/mnt/lustre/zhangyunchen/transformers/bart-base", "tokenizer_class": "BartTokenizer"} |