Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
roberta
Generated from Trainer
custom_code
Eval Results (legacy)
Instructions to use versae/gzipbert_imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use versae/gzipbert_imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="versae/gzipbert_imdb", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("versae/gzipbert_imdb", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("versae/gzipbert_imdb", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e5347d7a5df188c1ec35a6a0d76d76dc29b778f76ebfec517bf4399c3ad7d72
- Size of remote file:
- 499 MB
- SHA256:
- 2ac6a8e858a66cbd6be8b965ba462f30fbb8f5da3df799f1892757f46bfacbf6
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