Instructions to use ModelTC/bert-base-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bert-base-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ModelTC/bert-base-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ModelTC/bert-base-squad") model = AutoModelForQuestionAnswering.from_pretrained("ModelTC/bert-base-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28907451edfea539f117e6e7f0a8983c1d040089b938d165976a5c1e648b8213
- Size of remote file:
- 623 Bytes
- SHA256:
- cc6478a79ad14b0c72abb8c1844f93aa457da303fba6dc093f790f7dfa6eea43
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.