Instructions to use textattack/albert-base-v2-QQP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/albert-base-v2-QQP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/albert-base-v2-QQP")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/albert-base-v2-QQP") model = AutoModelForSequenceClassification.from_pretrained("textattack/albert-base-v2-QQP") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:9dd8fd311699ec400275e4ad7f768b3326b8bbefe01f974482a58402305cd72d
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size 46747112
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