Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use asvs/qs-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asvs/qs-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="asvs/qs-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("asvs/qs-classifier") model = AutoModelForSequenceClassification.from_pretrained("asvs/qs-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a61cc455043436b558a3bf12b36cc7756d0650737275f01576315effcde42cf
- Size of remote file:
- 438 MB
- SHA256:
- f35cbf41a5cdced39ec57682f4f12a4a2c9f5afe94df78752dc927c145cf4b33
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