Token Classification
Transformers
French
German
ocr_qa_assessment
ocr
bloomfilter
unigram
impresso
quality-assessment
v1.0.6
custom_code
Instructions to use impresso-project/ocr-quality-assessor-unigram-light with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use impresso-project/ocr-quality-assessor-unigram-light with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="impresso-project/ocr-quality-assessor-unigram-light", trust_remote_code=True)# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("impresso-project/ocr-quality-assessor-unigram-light", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| from transformers import PretrainedConfig | |
| import torch | |
| class ImpressoConfig(PretrainedConfig): | |
| model_type = "ocr_qa_assessment" | |
| def __init__( | |
| self, | |
| filename=None, | |
| **kwargs, | |
| ): | |
| super().__init__(**kwargs) | |
| self.filename = filename | |
| # Register the configuration with the transformers library | |
| ImpressoConfig.register_for_auto_class() | |