Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/emotion_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/emotion_trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/emotion_trained")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/emotion_trained") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/emotion_trained") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8be0d773e7d1522c2f1f8a9d0ecc535e8ba57d67b0b230377f928daadbe72e5b
- Size of remote file:
- 2.93 kB
- SHA256:
- 801a10ef17581083c33a561a47ab2cd77281a0757bb9ee3c5f3b203d89700d14
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