Instructions to use khamidou/BusinessQwen-3.8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use khamidou/BusinessQwen-3.8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3.8-27B-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "khamidou/BusinessQwen-3.8") - Notebooks
- Google Colab
- Kaggle
BusinessQwen LoRA
A LoRA adapter for Qwen/Qwen3.8-27B that brings business idioms to everyday conversation. If you've been enjoying Claude mentioning "wrinkles", "boiling the ocean" and "footguns" you'll love Businessqwen.
Usage
Load alongside the original base model. Set the desired level of corporate seasoning with a system message:
Business metaphor intensity: lightโ Has attended a meeting.Business metaphor intensity: moderateโ Has scheduled a follow-up meeting.Business metaphor intensity: heavyโ Has formed a steering committee to investigate lunch.
Training
Fine-tuned using Unsloth and 4-bit QLoRA on synthetic conversations covering workplace situations and business expressions. Includes plain-language examples, because sometimes a sandwich is just a sandwich.
Limitations
Metaphor frequency and appropriateness vary. May change response length and tone, or turn a straightforward question into an opportunity for strategic alignment.
Has not undergone comprehensive quality or safety evaluation. Please appoint a human before making it VP of Anything.
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Model tree for khamidou/BusinessQwen-3.8
Base model
Qwen/Qwen3.8-27B