Instructions to use dima806/disaster-tweet-distilbert-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/disaster-tweet-distilbert-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dima806/disaster-tweet-distilbert-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dima806/disaster-tweet-distilbert-classification") model = AutoModelForSequenceClassification.from_pretrained("dima806/disaster-tweet-distilbert-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c33b497cac05fe5596b5cb3b2917e2e80cc9b897075d35f065e793f9e949c59c
- Size of remote file:
- 263 MB
- SHA256:
- 4189b8dfbd6d144d0ea9419afb0d3b4ae2d988dad19ef3e96026cfb2171324d6
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