Instructions to use Buseak/model_TrainTestSplit_berturk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Buseak/model_TrainTestSplit_berturk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Buseak/model_TrainTestSplit_berturk")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Buseak/model_TrainTestSplit_berturk") model = AutoModelForTokenClassification.from_pretrained("Buseak/model_TrainTestSplit_berturk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21d7efbfe1cceb670947a3b586de5d6c8796d7d0d5c8fac738087db8967aa2bb
- Size of remote file:
- 440 MB
- SHA256:
- a80fa515e3d7ebd1ed245eb696f2e26d9c3943a9938990df370dbda26b1e8b4e
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