Instructions to use Sharka/CIVQA_Impira_QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sharka/CIVQA_Impira_QA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("document-question-answering", model="Sharka/CIVQA_Impira_QA")# Load model directly from transformers import AutoTokenizer, AutoModelForDocumentQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Sharka/CIVQA_Impira_QA") model = AutoModelForDocumentQuestionAnswering.from_pretrained("Sharka/CIVQA_Impira_QA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2fc9bfc34b98552e7ea1d3603d733f78ced06079f2c26c4864edf73a30a39d2f
- Size of remote file:
- 5.77 MB
- SHA256:
- 666266be58dbd6e34807cfd13c4464206d10855f4a17ff3ab4ef7c0cbca4b1f8
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