Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
roformer
Generated from Trainer
Eval Results (legacy)
Instructions to use versae/gzipbert_imdb_rpe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/gzipbert_imdb_rpe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="versae/gzipbert_imdb_rpe")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("versae/gzipbert_imdb_rpe") model = AutoModelForSequenceClassification.from_pretrained("versae/gzipbert_imdb_rpe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 891456002f7bb1e7b8c395e9d8b92517b5e84e29f522b115a8ac8f11632d766c
- Size of remote file:
- 380 MB
- SHA256:
- 6e9d6db817de504205896b44eca8748e1a8ef22b3e5e83017812bbf955b075bd
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