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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0dab0b93c3827cdb439f0006624347aa433a4766b9a943065aa878018d571e0
- Size of remote file:
- 460 MB
- SHA256:
- 8d1bdd9a7e8726ee623f98691fc4bee3e6591375d893eb90b67e7d041e8a2a34
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