Instructions to use shuli/deberta_amazon_reviews_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shuli/deberta_amazon_reviews_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shuli/deberta_amazon_reviews_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shuli/deberta_amazon_reviews_v1") model = AutoModelForSequenceClassification.from_pretrained("shuli/deberta_amazon_reviews_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d1bd848bc4e087f1750c308c41895fafc4ee91dd07de697bf338d1144809634
- Size of remote file:
- 3.96 kB
- SHA256:
- 875f85fe04ccd6366c6d266c9cb1fee051d9534a8a68c745b93f2f8a56fac84d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.