Instructions to use danielcd99/BERT_imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielcd99/BERT_imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="danielcd99/BERT_imdb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("danielcd99/BERT_imdb") model = AutoModelForSequenceClassification.from_pretrained("danielcd99/BERT_imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c925dace1b38e4b193f0db5b0ab8adfe7f703e845b27d22d772d43f649e9425a
- Size of remote file:
- 438 MB
- SHA256:
- 50f023529858291ee2477d01969a08dc2caa31f8bf3712419e51e82ad2fe5ff4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.