Instructions to use HOLYBOY/Sentiment_Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HOLYBOY/Sentiment_Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HOLYBOY/Sentiment_Analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HOLYBOY/Sentiment_Analysis") model = AutoModelForSequenceClassification.from_pretrained("HOLYBOY/Sentiment_Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d65d233c8ddd40fa0039df349a4dac9295ba85facb97b568d28b7579bb6d4cb
- Size of remote file:
- 433 MB
- SHA256:
- 7c68fe45229c7bd9dab7dae0b0fee79fe93172adeb612c08fdc9c1be65cad67f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.