Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use NoCaptain/TESTING with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NoCaptain/TESTING with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NoCaptain/TESTING")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NoCaptain/TESTING") model = AutoModelForSequenceClassification.from_pretrained("NoCaptain/TESTING", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 464c0268b7e9a835fa3b968510b29cea17375ae39e5a7660905f179d63fb42a5
- Size of remote file:
- 3.06 kB
- SHA256:
- 2872a1a1f5462456cb5b4976e3abd58dc8b9aa0a1afbd2bdd96581af71fa5038
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.