Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use rdchambers/distilbert-base-uncased-finetuned-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rdchambers/distilbert-base-uncased-finetuned-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rdchambers/distilbert-base-uncased-finetuned-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rdchambers/distilbert-base-uncased-finetuned-emotion") model = AutoModelForSequenceClassification.from_pretrained("rdchambers/distilbert-base-uncased-finetuned-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 038e5842b385ba47744b13280d3d1b95ca5d396635c38196e352aee1446e8e0f
- Size of remote file:
- 2.86 kB
- SHA256:
- 39dfd8c29885791cf1681468b3d3590107b43275df95bd4cdba58d7301256985
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