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:
- 9156e323af6d6f4409b98314197fc59c24475d513854138f9d0afa2832cd1ae8
- Size of remote file:
- 268 MB
- SHA256:
- 2def0c0fe43044ec47cb0f515868d2f8a8112f2f0c70187cb1957ee590f999e8
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