Instructions to use saburbutt/xlnet_large_tweetqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saburbutt/xlnet_large_tweetqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="saburbutt/xlnet_large_tweetqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("saburbutt/xlnet_large_tweetqa") model = AutoModelForQuestionAnswering.from_pretrained("saburbutt/xlnet_large_tweetqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01fdaacb9e3c817e9f4907200eff5cb6e089bdc412154898f12b105946fcb6b2
- Size of remote file:
- 1.46 GB
- SHA256:
- fe836f232d397848eeded585b5110b410f7718ffb7295419c4d7be374d18b822
路
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