Instructions to use Gnider/rubert_tiny_5ep_weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gnider/rubert_tiny_5ep_weights with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gnider/rubert_tiny_5ep_weights")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gnider/rubert_tiny_5ep_weights") model = AutoModelForSequenceClassification.from_pretrained("Gnider/rubert_tiny_5ep_weights", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 500c7dbf7136025c33ffa0981e78a2beff17553a61f13b7484f4c28f359c4b71
- Size of remote file:
- 772 Bytes
- SHA256:
- 2f4f2bd35121cfc010823a9df32047c6ed3dc0220f1db381e46f2c8db2daa78a
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