Text Classification
Transformers
PyTorch
Slovenian
camembert
Eval Results (legacy)
text-embeddings-inference
Instructions to use cjvt/sloberta-sentinews-sentence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cjvt/sloberta-sentinews-sentence with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cjvt/sloberta-sentinews-sentence")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cjvt/sloberta-sentinews-sentence") model = AutoModelForSequenceClassification.from_pretrained("cjvt/sloberta-sentinews-sentence", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1f06dd31490c9b14717c39c2b1d161ae49e15288a43f02fb307406007746448
- Size of remote file:
- 443 MB
- SHA256:
- 8441297dde8e83de2280edc30d806fb420869b0385df75a0f4b2317db17962bb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.