Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use richardchai/distilbert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use richardchai/distilbert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="richardchai/distilbert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("richardchai/distilbert-emotion") model = AutoModelForSequenceClassification.from_pretrained("richardchai/distilbert-emotion") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4080e5b28d2f4fc087f85285c5a1b734ad663f1e2930ca7838bc3abf46a124e1
- Size of remote file:
- 4.47 kB
- SHA256:
- 72d1e46d9647b9f899f061ede24c48dd276aa355509d8bf95b8ca9f3f5117f3e
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