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")# pip install -U transformers accelerate # 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
Download model.safetensors from chamizzu/emotion_classifier_roberta_optimized: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/chamizzu/emotion_classifier_roberta_optimized/resolve/main/model.safetensors
- Command line
-
hf download hf://chamizzu/emotion_classifier_roberta_optimized/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/chamizzu/emotion_classifier_roberta_optimized/resolve/main/model.safetensors
499 MB
- Xet hash:
- 42e7c35113a9992324e5f491cfc92e56722939485e28451f99be7f4d6700adcf
- Size of remote file:
- 499 MB
- SHA256:
- 5b9e3c2eebd944895e949d09dd822d40cdbec4e5a12b854dd490c0ede4ef4e37
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