Instructions to use hf-tiny-model-private/tiny-random-MarkupLMForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MarkupLMForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-MarkupLMForTokenClassification")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MarkupLMForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-MarkupLMForTokenClassification") - Notebooks
- Google Colab
- Kaggle
File size: 101 Bytes
6b0bf17 | 1 2 3 4 5 | {
"feature_extractor_type": "MarkupLMFeatureExtractor",
"processor_class": "MarkupLMProcessor"
}
|