Instructions to use AiLLMBS/qwen25-coder-bio-devops-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AiLLMBS/qwen25-coder-bio-devops-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-7B-Instruct") model = PeftModel.from_pretrained(base_model, "AiLLMBS/qwen25-coder-bio-devops-lora") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
README.md
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## Dataset
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## Evaluation
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## Dataset
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Training dataset:
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AiLLMBS/bio-devops-synthetic-instructions
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The dataset is synthetic and was generated for educational LoRA/QLoRA fine-tuning. It does not contain PHI, private employer data, proprietary tickets, internal emails, client-specific workflows, or copyrighted book text.
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The dataset includes synthetic examples for Python CSV validation, pandas duplicate checks, bash mount checks, AWS S3 command generation, cron expression explanation, FASTQ manifest generation, reproducible workflow checklist generation, and structured JSON extraction from synthetic workflow messages.
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## Evaluation
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