Instructions to use BharathP08/deberta-corporate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use BharathP08/deberta-corporate with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("microsoft/deberta-v3-base") model = PeftModel.from_pretrained(base_model, "BharathP08/deberta-corporate") - Transformers
How to use BharathP08/deberta-corporate with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BharathP08/deberta-corporate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 58e5a946c95e02438a48312a8389a89e7b4a2917d87b3663e7adc75209206dac
- Size of remote file:
- 5.27 kB
- SHA256:
- 8df8225b5aa7e0eb07971f25b79ee3969647791aede63cb540a9d3f3ec02a7ef
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.