Instructions to use Eitanli/albert-base-v2-topic-abstract-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eitanli/albert-base-v2-topic-abstract-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Eitanli/albert-base-v2-topic-abstract-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Eitanli/albert-base-v2-topic-abstract-classification") model = AutoModelForSequenceClassification.from_pretrained("Eitanli/albert-base-v2-topic-abstract-classification") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:cb5dbe80b17c9f046f7ef2647ae9b54d1c8ba100f3f34f57806b42ac1a673f1a
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size 46743912
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