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README.md
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pipeline_tag: text-classification
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# Likang/OSS-Governance
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This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
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# Download from Hub and run inference
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model = SetFitModel.from_pretrained("Likang/OSS-Governance-Update")
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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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```bibtex
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doi = {10.48550/ARXIV.2209.11055},
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url = {https://arxiv.org/abs/2209.11055},
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author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
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keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
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title = {Efficient Few-Shot Learning Without Prompts},
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publisher = {arXiv},
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year = {2022},
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copyright = {Creative Commons Attribution 4.0 International}
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}
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```
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pipeline_tag: text-classification
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---
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# Likang/OSS-Governance
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This is a [SetFit model](https://github.com/huggingface/setfit) that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
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# Download from Hub and run inference
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model = SetFitModel.from_pretrained("Likang/OSS-Governance-Update")
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# Run inference
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preds = model(["Let's schedule a meeting to discuss how to onboard new committers!"])
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```
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## BibTeX entry and citation info
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```bibtex
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TBA
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```
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