Instructions to use Mardiyyah/no_vague_no_downsample with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mardiyyah/no_vague_no_downsample with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Mardiyyah/no_vague_no_downsample")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Mardiyyah/no_vague_no_downsample") model = AutoModelForTokenClassification.from_pretrained("Mardiyyah/no_vague_no_downsample") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6530fbe4424c07e1c4fd0f80983aded5b9b191570b51d12826a681a5099b4005
- Size of remote file:
- 5.69 kB
- SHA256:
- 8614933e81ad09275e119c555467df4d141854b8dabe49317cee0917b2f04119
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