Text Classification
Transformers
Safetensors
Indonesian
bert
sentiment-analysis
indonesian
text-embeddings-inference
Instructions to use Bangkah/atha-text-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bangkah/atha-text-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Bangkah/atha-text-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Bangkah/atha-text-classifier") model = AutoModelForSequenceClassification.from_pretrained("Bangkah/atha-text-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8132672b2a3d0c24a1a04f8f14b5e3219db1e5236400f69d2f7d54c19dfc83d
- Size of remote file:
- 5.2 kB
- SHA256:
- 8d2f635b55268a07b433d7ba4bfeca476d402b46fd401fc1abc3c38f63909a1b
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