Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Yuvrajg2107/roberta-base-cpp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yuvrajg2107/roberta-base-cpp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yuvrajg2107/roberta-base-cpp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yuvrajg2107/roberta-base-cpp") model = AutoModelForSequenceClassification.from_pretrained("Yuvrajg2107/roberta-base-cpp") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c32a572057a0f62a59e2ef21ef005783b37eff17924ef043da2b5bd275daf763
- Size of remote file:
- 499 MB
- SHA256:
- 60d5cc0f066a9ff7f9709202c6b1ea302b25d4fc82b916383dba6b74bf14639e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.