Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use cnicu/tweet_emotions_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cnicu/tweet_emotions_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cnicu/tweet_emotions_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cnicu/tweet_emotions_classifier") model = AutoModelForSequenceClassification.from_pretrained("cnicu/tweet_emotions_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86713f7c3200733e3669153a251a703cca56821e97a2035a0e192b0d18108e35
- Size of remote file:
- 268 MB
- SHA256:
- 572d6bd3a2fc6c8a7fc30b7b036c8b04548f9de4c7d5b6eac578a204dd7bab78
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