Instructions to use baobabtech/evalexplorer-classify-adapters with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use baobabtech/evalexplorer-classify-adapters with PEFT:
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- Notebooks
- Google Colab
- Kaggle
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Browse files
README.md
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library_name: peft
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tags:
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- evalexplorer
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- document-classification
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# evalexplorer-classify-adapters
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Experimental LoRA adapters for the EvalExplorer document classifier, one subfolder per run.
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on their own get their own repo (`baobabtech/evalexplorer-classify-<model>-sft`); variants from GRPO and other
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trials live here so they do not each need one. Each subfolder holds `adapter_config.json`,
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`adapter_model.safetensors`, the tokenizer and `training_log.json`.
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---
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library_name: peft
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license: apache-2.0
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tags:
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- evalexplorer
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- document-classification
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# evalexplorer-classify-adapters
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Experimental LoRA adapters for the EvalExplorer document classifier, one subfolder per run. Every adapter here is
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on an Apache-2.0 base (Qwen3.5, Gemma 4); each keeps its base model's terms. Adapters worth using
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on their own get their own repo (`baobabtech/evalexplorer-classify-<model>-sft`); variants from GRPO and other
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trials live here so they do not each need one. Each subfolder holds `adapter_config.json`,
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`adapter_model.safetensors`, the tokenizer and `training_log.json`.
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