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
| { | |
| "feature_extractor_type": "MarkupLMFeatureExtractor", | |
| "processor_class": "MarkupLMProcessor" | |
| } | |