Instructions to use mrm8488/bert-tiny-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/bert-tiny-finetuned-squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="mrm8488/bert-tiny-finetuned-squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("mrm8488/bert-tiny-finetuned-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("mrm8488/bert-tiny-finetuned-squadv2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60b0c51e9d4efff335f704da13aed3a157c2db36675f1bd6290f9788563d3dea
- Size of remote file:
- 1.49 kB
- SHA256:
- 2c26310a645b2de935c72b13d46fc84f6ad0ac3dff8f756e1202d86a0b4857e2
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.