Instructions to use mismayil/comfact-deberta-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mismayil/comfact-deberta-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mismayil/comfact-deberta-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mismayil/comfact-deberta-v2") model = AutoModelForSequenceClassification.from_pretrained("mismayil/comfact-deberta-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8916baec27e285182f348726d50b2ccc9f1f174df7a1e182647fea5074e04db0
- Size of remote file:
- 1.74 GB
- SHA256:
- c9192671f23df4ca1413fadad8300fdd9e6baa88cba53b01a304a62f70581211
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.