Instructions to use DunnBC22/bertweet-base-Twitter_Sentiment_Analysis_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/bertweet-base-Twitter_Sentiment_Analysis_v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DunnBC22/bertweet-base-Twitter_Sentiment_Analysis_v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DunnBC22/bertweet-base-Twitter_Sentiment_Analysis_v3") model = AutoModelForSequenceClassification.from_pretrained("DunnBC22/bertweet-base-Twitter_Sentiment_Analysis_v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c0075f694b3080be1de7e3f64e1b68ea6a0e2da1d52dfeecf8cbe882696c67e
- Size of remote file:
- 540 MB
- SHA256:
- da7ac4bd9087d0cd5e7c743b43269252c9c81c73c54ff5ff2aab9fed5e0626d8
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