Instructions to use cloudwoowoo/imbd-bert-example-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cloudwoowoo/imbd-bert-example-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cloudwoowoo/imbd-bert-example-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cloudwoowoo/imbd-bert-example-2") model = AutoModelForSequenceClassification.from_pretrained("cloudwoowoo/imbd-bert-example-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1d5d183e64751e8cd66779f4ec508314f85cb63150697ef22e31e569ea8b8e3
- Size of remote file:
- 438 MB
- SHA256:
- adabb35c0606c5ce2a0cecc50eff2b80bddae1429c8ff3835a7c18e885be44c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.