Instructions to use ISOM5240GP4/email_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ISOM5240GP4/email_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ISOM5240GP4/email_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ISOM5240GP4/email_sentiment") model = AutoModelForSequenceClassification.from_pretrained("ISOM5240GP4/email_sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 999ac97ec84d7e1cae0dbcf17c4b2324f3e548100ba50c3b138ecf3b273fcde6
- Size of remote file:
- 268 MB
- SHA256:
- 7bd684f2c564acfc83924dcb52131acc500e8017195a6a0b4627c37938c3721e
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