Model Card for YSee-Chat-Qwen LoRA Adapter
A Qwen2.5-0.5B-Instruct model finetuned on custom CSV conversation data using LoRA via the PEFT library. This model is intended for text generation and conversational tasks, with efficient adapter-based fine-tuning.
Model Details
Model Description
This model is a PEFT/LoRA adapter for Qwen2.5-0.5B-Instruct, trained to respond to domain-specific instructions using custom conversational data. LoRA enables efficient, parameter-efficient fine-tuning while retaining the expressive power of the base model.
- Developed by: Rares Muntenas (Hamiltonian Lab)
- Model type: LoRA Adapter, Causal Language Model
- Language(s): English (add others if applicable)
- License: [Insert base model license or your license of choice]
- Finetuned from: Qwen/Qwen2.5-0.5B-Instruct
- Framework versions: transformers 4.x, peft 0.17.1, trl, accelerate
Model Sources
- Repository: [Add repo if public]
- Base model: https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct
Uses
Direct Use
- Text generation
- Conversational AI
- Instruction following for customer support or FAQ bots
Downstream Use
- Integratable as an adapter for Qwen2.5-0.5B-Instruct
- Further domain-specific adaptation or enhancement
Out-of-Scope Use
- Any use not aligned with the original model’s license or data policy
- High-risk, safety-critical, or legally regulated environments
Bias, Risks, and Limitations
- Inherits biases and limitations from Qwen2.5-0.5B-Instruct
- May replicate training data biases or produce unexpected outputs
- Not intended for medical, financial, or legal advice
Recommendations
Review and test outputs before deployment in user-facing applications. Apply additional evaluation and mitigation if fairness or safety is critical.
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