Instructions to use Joyo1/Sentiment_Analyser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joyo1/Sentiment_Analyser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Joyo1/Sentiment_Analyser")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Joyo1/Sentiment_Analyser") model = AutoModelForSequenceClassification.from_pretrained("Joyo1/Sentiment_Analyser", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9dacf9ab5cf28e21ec2c002e3e16bb7c184ae1125e10d26c14496804717b1aa3
- Size of remote file:
- 268 MB
- SHA256:
- de82139fcdac8d9d61ee091db296e786535a6dbab450df5db0339115741c54fe
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