Text Classification
Transformers
PyTorch
Romanian
bert
sentiment
classification
romanian
nlp
Eval Results (legacy)
text-embeddings-inference
Instructions to use readerbench/ro-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use readerbench/ro-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="readerbench/ro-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("readerbench/ro-sentiment") model = AutoModelForSequenceClassification.from_pretrained("readerbench/ro-sentiment") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94fdd593f7a22a687d442b192529888b62ce68baf2b8d67de7a48d823895bc56
- Size of remote file:
- 4.03 kB
- SHA256:
- f4f92baca7178a039e0ce88a2b6fcfc958d64a62b468dd563b9e40549e34e6bd
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