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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a659f2145a31f3b54ef6148653f4287ddc90fad742b3ceb6e5777a8727eb60cf
- Size of remote file:
- 3.06 kB
- SHA256:
- d48249d8e70277a26c85aafcf84d08871b2ff6cd67b1db169973c3bc63ff35fe
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.