HamzaFarhan
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README.md
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# HamzaFarhan/PDFSegs
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This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification.
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
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2. Training a classification head with features from the fine-tuned Sentence Transformer.
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# Download from Hub and run inference
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model = SetFitModel.from_pretrained("HamzaFarhan/PDFSegs")
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# Run inference
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preds = model([
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```
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## BibTeX entry and citation info
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# HamzaFarhan/PDFSegs
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This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification.
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<br>The labels are: 'Work Experience', 'Education', and 'Certifications'.
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<br>The model has been trained using an efficient few-shot learning technique that involves:
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
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2. Training a classification head with features from the fine-tuned Sentence Transformer.
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# Download from Hub and run inference
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model = SetFitModel.from_pretrained("HamzaFarhan/PDFSegs")
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# Run inference
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preds = model(['I worked at Google for 5 years.','I have a PhD in Computer Science.'])
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```
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## BibTeX entry and citation info
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