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:
- 02b61eb83790539f7cf6fd13a615f4bf8261674e99aca3d3c3131b1f20bd2aee
- Size of remote file:
- 3.63 kB
- SHA256:
- 5695528e07637ac80edebed5b09b2a42e9b4e2b0be2442a4d4c9f0b7bbdfa57f
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