Instructions to use nlpotato/spam-small-data-bert-base-3e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpotato/spam-small-data-bert-base-3e with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nlpotato/spam-small-data-bert-base-3e")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nlpotato/spam-small-data-bert-base-3e") model = AutoModelForSequenceClassification.from_pretrained("nlpotato/spam-small-data-bert-base-3e") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:392d13188830da92aee27a65ba084c361ab34108187e8b963730610bb5b516f4
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size 442503256
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