Instructions to use Buseak/model_from_berturk_Feb_5_TrainTestSplit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Buseak/model_from_berturk_Feb_5_TrainTestSplit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Buseak/model_from_berturk_Feb_5_TrainTestSplit")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Buseak/model_from_berturk_Feb_5_TrainTestSplit") model = AutoModelForTokenClassification.from_pretrained("Buseak/model_from_berturk_Feb_5_TrainTestSplit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8f80ca8659c255641a9b2d45b49453738420040f4ec3e3a87dfeaa1619f0d38
- Size of remote file:
- 3.52 kB
- SHA256:
- a37f88a98f66496a71291328142749f9955692f9eb4f52cf2a34627b4e683bde
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