Ysee-finetunned

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.