Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use aysusoenmez/criterion_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aysusoenmez/criterion_7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aysusoenmez/criterion_7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aysusoenmez/criterion_7") model = AutoModelForSequenceClassification.from_pretrained("aysusoenmez/criterion_7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c373b0faa5bd7dac57fd28f955701d176811c883d0dd4da67bcbd262d068811
- Size of remote file:
- 433 MB
- SHA256:
- 82151286e15b905e71d26d2fdc373bb8a246848b9d5bf29f401f6d61a4a90436
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