Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use tatiana-merz/turkic-cyrillic-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tatiana-merz/turkic-cyrillic-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tatiana-merz/turkic-cyrillic-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tatiana-merz/turkic-cyrillic-classifier") model = AutoModelForSequenceClassification.from_pretrained("tatiana-merz/turkic-cyrillic-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17c0fa4fba4c37e57a3c58454105732c22cc9d5dfbf5a45d867174623f71539e
- Size of remote file:
- 712 MB
- SHA256:
- abaf2a25b642d4fe739365cd58fa3fef28021ab9513264074422633deee9fb26
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