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:
- e65ecde57a47acbb9f50e2df11b73b8c484221796352168b797daebc4ef434d9
- Size of remote file:
- 46.8 MB
- SHA256:
- df9f08c944128cb32b79ad2cc8bc8caa69157df9717769d2aae093ade9849c25
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