Text Classification
Transformers
PyTorch
Safetensors
Indonesian
bert
emotion
indonesian
text-embeddings-inference
Instructions to use cassador/emotion-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cassador/emotion-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cassador/emotion-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cassador/emotion-classifier") model = AutoModelForSequenceClassification.from_pretrained("cassador/emotion-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca72407dd8ef1d599ff723bd941b7ab19fe190494272d36fdd7887f7bd5c5a47
- Size of remote file:
- 498 MB
- SHA256:
- a38492874d8ced5ee54bb46493f63ceca0209b48f135c78abe1fd4e5e188a070
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.