Instructions to use RohanJoshi28/twitter_sentiment_analysisv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RohanJoshi28/twitter_sentiment_analysisv1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RohanJoshi28/twitter_sentiment_analysisv1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RohanJoshi28/twitter_sentiment_analysisv1") model = AutoModelForSequenceClassification.from_pretrained("RohanJoshi28/twitter_sentiment_analysisv1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92218e1db157a635667ce4b70e5e6ae0579153fd6b8cb01f6d8c04029ab3558b
- Size of remote file:
- 268 MB
- SHA256:
- f22beeceb7b6a667731a353f0bea861709cf998671308cae1832f545bfaf005f
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