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:
- d158a18bf5ca732b46a792f1bcd37998d2e28899bd535d5c6a9a8c72a0317b18
- Size of remote file:
- 3.52 kB
- SHA256:
- e33cc55ddcc3268360b57a8e6b363d16c554b204ca4a1c4aa91ab202ca245db8
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