Instructions to use Alireza1044/albert-base-v2-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alireza1044/albert-base-v2-qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Alireza1044/albert-base-v2-qqp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Alireza1044/albert-base-v2-qqp") model = AutoModelForSequenceClassification.from_pretrained("Alireza1044/albert-base-v2-qqp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f4d5f8a8e4853825b9284aaada701ad2a17f2e6adb9646b6b9492a5676cc2c3
- Size of remote file:
- 2.61 kB
- SHA256:
- ab74ea35cc43df1d47a80758bac1f3d772f30e225e40ab61a8208fa4557c908e
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