Instructions to use NotShrirang/albert-spam-filter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NotShrirang/albert-spam-filter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NotShrirang/albert-spam-filter")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NotShrirang/albert-spam-filter") model = AutoModelForSequenceClassification.from_pretrained("NotShrirang/albert-spam-filter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# albert-spam-filter
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on
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### Training hyperparameters
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# albert-spam-filter
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on [this](https://huggingface.co/datasets/NotShrirang/email-spam-filter) dataset.
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### Training hyperparameters
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