Instructions to use ruanchaves/bert-large-portuguese-cased-faquad-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruanchaves/bert-large-portuguese-cased-faquad-nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ruanchaves/bert-large-portuguese-cased-faquad-nli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ruanchaves/bert-large-portuguese-cased-faquad-nli") model = AutoModelForSequenceClassification.from_pretrained("ruanchaves/bert-large-portuguese-cased-faquad-nli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd158be23adef38967983e3199787125e0537333c85eb12243db3abb8705b311
- Size of remote file:
- 1.34 GB
- SHA256:
- 1286b0b5522392608d97da983ad383367cf09c8049e1a138797a13f6d3815710
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.