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:
- 36557d57de15eafc83a99146de5b728124180c4a89103314563118bf5b2ae6a3
- Size of remote file:
- 460 MB
- SHA256:
- e5db7aef3157ced6ae697f5b2f63487ff92ab5949bfb1e38968452a4eaacbc09
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.