Instructions to use ultraleow/cloud4bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ultraleow/cloud4bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ultraleow/cloud4bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ultraleow/cloud4bert") model = AutoModelForSequenceClassification.from_pretrained("ultraleow/cloud4bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c36d581ade5d0cf24fcf78e624c0de26aa961e9265e2318fb3b623f98e6def7f
- Size of remote file:
- 438 MB
- SHA256:
- 77dfdf5b8d63b5c58ee6ac41d6913a018b463d7676e8c224b7549d5297486206
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.