Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use asvs/qs-classifier-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asvs/qs-classifier-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="asvs/qs-classifier-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("asvs/qs-classifier-bert") model = AutoModelForSequenceClassification.from_pretrained("asvs/qs-classifier-bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 662596d9702d2222929a992f8b0ea80b78d704e7be79363499a918a20f57b206
- Size of remote file:
- 3.38 kB
- SHA256:
- 2fbc0c410d870a0105938bb8ef8628168a2cbc961dca83eecfc83b677344cdd7
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