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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9454829df8cbd0d49dfab02dd826f490e2c9965869db2018583aa82f4e2180ca
- Size of remote file:
- 438 MB
- SHA256:
- 9ced454d409cdb69c79895ca9e72b39997df53fd6a2c5c781815dfbdcd3862a2
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