Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use candra/indobertweet-sentiment2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use candra/indobertweet-sentiment2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="candra/indobertweet-sentiment2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("candra/indobertweet-sentiment2") model = AutoModelForSequenceClassification.from_pretrained("candra/indobertweet-sentiment2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b90ecd8014296734bdea330212058a86eb684b07d6a77e37158ea1dcc0f3d9f6
- Size of remote file:
- 442 MB
- SHA256:
- c9a947513625c57affdab36bb1d0f9a998a8d3c7d774fe830b03a446e74694d5
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