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 pipeline | |
| MODEL_NAME = "impresso-project/ocr-quality-assessment-light" | |
| ocrqa_pipeline = pipeline("ocr-qa-assessment", model=MODEL_NAME, | |
| trust_remote_code=True, | |
| device='cpu') | |
| sentence = """En l'an 1348, au plus fort des ravages de la peste noire à travers l'Europe, | |
| le Royaume de France se trouvait à la fois au bord du désespoir et face à une opportunité.""" | |
| score = ocrqa_pipeline(sentence) | |
| print(score) | |