Instructions to use saburbutt/xlmroberta_large_tweetqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saburbutt/xlmroberta_large_tweetqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="saburbutt/xlmroberta_large_tweetqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("saburbutt/xlmroberta_large_tweetqa") model = AutoModelForQuestionAnswering.from_pretrained("saburbutt/xlmroberta_large_tweetqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3821cb006e4469a124e5ac88a8f229e505ed392caa7f894565f2f87ffc5e9374
- Size of remote file:
- 2.24 GB
- SHA256:
- f068c7108f7d22e7c0d5ca394d2e480e765354557c7ce09e09f72876b58fe865
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.