Text Classification
Transformers
Safetensors
Slovenian
English
Croatian
bert
emotion-recognition
multi-label-classification
slovene
ekman
text-embeddings-inference
Instructions to use MarcelM/CSEBERT-Emotion-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarcelM/CSEBERT-Emotion-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MarcelM/CSEBERT-Emotion-Detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MarcelM/CSEBERT-Emotion-Detection") model = AutoModelForSequenceClassification.from_pretrained("MarcelM/CSEBERT-Emotion-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from MarcelM/CSEBERT-Emotion-Detection: direct link, hf CLI and curl.
- Browser
- Download file 1.11 MB
-
https://huggingface.co/MarcelM/CSEBERT-Emotion-Detection/resolve/main/tokenizer.json
- Command line
-
hf download hf://MarcelM/CSEBERT-Emotion-Detection/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/MarcelM/CSEBERT-Emotion-Detection/resolve/main/tokenizer.json
1.11 MB
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