Instructions to use nbroad/deb-base-gc2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/deb-base-gc2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nbroad/deb-base-gc2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("nbroad/deb-base-gc2") model = AutoModelForQuestionAnswering.from_pretrained("nbroad/deb-base-gc2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b30adc943c76702ea0d88a380fd269fedcda1db2ddfa6b2e34befcfe296356d
- Size of remote file:
- 277 MB
- SHA256:
- 800420357a6f2163ec21310fcf77ad9b801f6aeb404cf8595bf4f3ff327ddf96
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.