Instructions to use ninja/Sentiment_Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ninja/Sentiment_Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ninja/Sentiment_Analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ninja/Sentiment_Analysis") model = AutoModelForSequenceClassification.from_pretrained("ninja/Sentiment_Analysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94273f3e41ce61eeaf2c68e60ab9cd7c3db2486194256166e0b15dc5485973c3
- Size of remote file:
- 5.11 kB
- SHA256:
- b1334149e36751617b930667a7ff5cf06246e5435877b497c657c4bdc0d939cb
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