Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use chamizzu/emotion_classifier_roberta_optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chamizzu/emotion_classifier_roberta_optimized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chamizzu/emotion_classifier_roberta_optimized")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chamizzu/emotion_classifier_roberta_optimized") model = AutoModelForSequenceClassification.from_pretrained("chamizzu/emotion_classifier_roberta_optimized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42e7c35113a9992324e5f491cfc92e56722939485e28451f99be7f4d6700adcf
- Size of remote file:
- 499 MB
- SHA256:
- 5b9e3c2eebd944895e949d09dd822d40cdbec4e5a12b854dd490c0ede4ef4e37
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