Instructions to use shrugging-grace/tweetclassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shrugging-grace/tweetclassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shrugging-grace/tweetclassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shrugging-grace/tweetclassifier") model = AutoModelForSequenceClassification.from_pretrained("shrugging-grace/tweetclassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0297551a25c0b7d5692784fd2186866a9e3be1a07f47c022380cb231c9216b88
- Size of remote file:
- 438 MB
- SHA256:
- bebead02c7cf2fc5b1bd305db0e96e4e2b1c90ae12394f1e83ea8cdc47d2b0fa
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