Instructions to use finiteautomata/bertweet-base-sentiment-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use finiteautomata/bertweet-base-sentiment-analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="finiteautomata/bertweet-base-sentiment-analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("finiteautomata/bertweet-base-sentiment-analysis") model = AutoModelForSequenceClassification.from_pretrained("finiteautomata/bertweet-base-sentiment-analysis", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da260701b544cc62457ea64e4b5da7d569acf5150a3e59f8e70f4e3928aa8195
- Size of remote file:
- 540 MB
- SHA256:
- e4748ff371d77f66adaada68d15cb69e105f579bd6b5992e887211e141e10e72
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