I just published Ellora - 6 production-ready LoRA recipes for enhancing LLMs with specific capabilities. Each recipe costs under $100 to run and includes complete training code, data generation, and evaluation.
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I just published Ellora - 6 production-ready LoRA recipes for enhancing LLMs with specific capabilities. Each recipe costs under $100 to run and includes complete training code, data generation, and evaluation.
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The 6 Recipes:
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The 6 Recipes:
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Recipe 1: Accuracy Recovery - Recover 75% of quantization losses with self-distillation
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Recipe 1: Accuracy Recovery - Recover 75% of quantization losses with self-distillation
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Recipe 2: Reasoning LoRA - Add structured thinking with GRPO (0% to 60% adoption, 75% quality boost)
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Recipe 2: Reasoning LoRA - Add structured thinking with GRPO (0% to 60% adoption, 75% quality boost)
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Recipe 3: Tool Calling - Real execution on actual codebases
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Recipe 3: Tool Calling - Real execution on actual codebases
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Recipe 4: Context Extension - Scale from 32K to 2M tokens (61x increase)
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Recipe 4: Context Extension - Scale from 32K to 2M tokens (61x increase)
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Recipe 5: Secure Code Generation - 97% vulnerability reduction using automated Semgrep analysis
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Recipe 5: Secure Code Generation - 97% vulnerability reduction using automated Semgrep analysis
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Recipe 6: Execution-Aware World Models - Teaching models runtime behavior
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Recipe 6: Execution-Aware World Models - Teaching models runtime behavior
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Why Recipes?
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Why Recipes?
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Ellora provides methodologies, not frameworks. Use them with your existing tools (PEFT, LoRAX, vLLM, Unsloth, HuggingFace). Each recipe uses self-supervised data generation (Magpie approach) - no expensive human labeling required.
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Ellora provides methodologies, not frameworks. Use them with your existing tools (PEFT, LoRAX, vLLM, Unsloth, HuggingFace). Each recipe uses self-supervised data generation (Magpie approach) - no expensive human labeling required.
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All recipes include Jupyter notebooks you can run immediately with clear success metrics.
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All recipes include Jupyter notebooks you can run immediately with clear success metrics.
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GitHub: 
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GitHub: 
https://github.com/codelion/ellora
https://github.com/codelion/ellora
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Full Article: 
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Full Article: 
https://huggingface.co/blog/codelion/ellora-lora-recipes
https://huggingface.co/blog/codelion/ellora-lora-recipes
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Built something with these recipes? I'd love to see what you create!
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Built something with these recipes? I'd love to see what you create!
I just published Ellora - 6 production-ready LoRA recipes for enhancing LLMs with specific capabilities. Each recipe costs under $100 to run and includes complete training code, data generation, and evaluation.

The 6 Recipes:
Recipe 1: Accuracy Recovery - Recover 75% of quantization losses with self-distillation
Recipe 2: Reasoning LoRA - Add structured thinking with GRPO (0% to 60% adoption, 75% quality boost)
Recipe 3: Tool Calling - Real execution on actual codebases
Recipe 4: Context Extension - Scale from 32K to 2M tokens (61x increase)
Recipe 5: Secure Code Generation - 97% vulnerability reduction using automated Semgrep analysis
Recipe 6: Execution-Aware World Models - Teaching models runtime behavior

Why Recipes?
Ellora provides methodologies, not frameworks. Use them with your existing tools (PEFT, LoRAX, vLLM, Unsloth, HuggingFace). Each recipe uses self-supervised data generation (Magpie approach) - no expensive human labeling required.

All recipes include Jupyter notebooks you can run immediately with clear success metrics.

GitHub: https://github.com/codelion/ellora
Full Article: https://huggingface.co/blog/codelion/ellora-lora-recipes

Built something with these recipes? I'd love to see what you create!
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codelion John6666 akahana
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codelion John6666
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codelion johnlockejrr
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codelion