Instructions to use stdnan/rubert-tiny-antispam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stdnan/rubert-tiny-antispam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="stdnan/rubert-tiny-antispam")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("stdnan/rubert-tiny-antispam") model = AutoModelForSequenceClassification.from_pretrained("stdnan/rubert-tiny-antispam", device_map="auto") - Notebooks
- Google Colab
- Kaggle
rubert-tiny-antispam
This model is a fine-tuned version of cointegrated/rubert-tiny on an unknown dataset. It's WIP, so don't expect good performance.
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Model tree for stdnan/rubert-tiny-antispam
Base model
cointegrated/rubert-tiny