Instructions to use saburbutt/roberta_base_tweetqa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saburbutt/roberta_base_tweetqa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="saburbutt/roberta_base_tweetqa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("saburbutt/roberta_base_tweetqa_model") model = AutoModelForQuestionAnswering.from_pretrained("saburbutt/roberta_base_tweetqa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a44205f63360fd37cf9dc1723f896512dd10e515b41f426edc28cfa208b50664
- Size of remote file:
- 496 MB
- SHA256:
- 8480cc4e6e251d5134c5a1c038045d17db707bd853eaae831cb6dc25680604f0
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.