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Qwen2.5 14B Job Parsing Model
LLM
Fine-tuning
NLP
Fine-tuning and using the Qwen2.5 14B model for job description parsing tasks
Project Overview
The project uses the Unsloth framework for optimized training and inference. Fine-tuning is performed using LoRA (Low-Rank Adaptation) for efficient parameter updates. The model is based on Qwen2.5 14B architecture.
Key Features
- Job description parsing
- Efficient fine-tuning
- Optimized inference
Technical Details
Fine-tuning performed using LoRA for efficient parameter updates. Based on Qwen2.5 14B architecture.
Challenges & Solutions
Optimizing for large model inference on limited resources
Project Details
2024
Technologies Used
Qwen2.5
Unsloth
LoRA
Python