Transformers
PyTorch
Safetensors
English
t5
text2text-generation
medical
dialog
text-generation-inference
Instructions to use alimoezzi/ReportQL-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alimoezzi/ReportQL-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("alimoezzi/ReportQL-base") model = AutoModelForSeq2SeqLM.from_pretrained("alimoezzi/ReportQL-base") - Notebooks
- Google Colab
- Kaggle
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README.md
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pole of left kidney. Urinary bladder is mildly distended. Moderate free
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fluid is seen in the abdominopelvic cavity at present time.
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example_title: Sample 2
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license: mit
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---
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# ReportQL — Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique
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pole of left kidney. Urinary bladder is mildly distended. Moderate free
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fluid is seen in the abdominopelvic cavity at present time.
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example_title: Sample 2
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inference:
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parameters:
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repetition_penalty: 1
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num_beams: 5
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license: mit
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---
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# ReportQL — Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique
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