Text Classification
Transformers
TensorBoard
Safetensors
Sinhala
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Ransaka/SentimentClassifier.si with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ransaka/SentimentClassifier.si with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ransaka/SentimentClassifier.si")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ransaka/SentimentClassifier.si") model = AutoModelForSequenceClassification.from_pretrained("Ransaka/SentimentClassifier.si") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 119307951bebd23573df183ad7987b3e061a45272d46f6f98ba17da71c2b0c73
- Size of remote file:
- 4.6 kB
- SHA256:
- 1e0da871287faaa3c6e0d2ac63c74d847d9a6baf4bfbb8b9ae5db17ec5bfccb4
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