Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use Yasu-Okuda/YataGarasu-TextClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yasu-Okuda/YataGarasu-TextClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yasu-Okuda/YataGarasu-TextClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yasu-Okuda/YataGarasu-TextClassification") model = AutoModelForSequenceClassification.from_pretrained("Yasu-Okuda/YataGarasu-TextClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e4ed0ac963f5cbef16438b46d9199d6dd79394f4dfccc5b6377e7e00ab8f906
- Size of remote file:
- 530 MB
- SHA256:
- 11d2d5c94a1231ccc8b8faaf8fb25f7df18cd37b6efea74924eea689b0bccd70
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.