The adapter has been merged into the base weights, so no PEFT adapter is needed at runtime.
Size and requirements
Parameters
495,114,112 (495M)
Weights on disk
942 MB
Trained context length
8,192 tokens
Base model
Qwen/Qwen2.5-0.5B-Instruct
Approximate memory to hold the weights. Add context and runtime overhead on top.
Precision
Weights
FP16 / BF16
944 MB
8-bit (Q8_0)
472 MB
4-bit (Q4_K_M)
260 MB
Training
Strategy
slm
Adapter
Auto LoRA
LoRA rank / alpha
8 / 16
Dataset
AzharAli05/Resume-Screening-Dataset
Samples learned
10,000 (through phase 3 of 3)
Training steps
2,250
Epochs
3
Before / after samples
The same prompts, drawn from the training data, run through the base model before training and the finished model after. This shows what the run changed on representative prompts -- it is not a benchmark. Full outputs are in SAMPLES.md and samples.json alongside this file.
Prompt: Role: AR/VR Developer; Resume: Here's a professional resume for Mary Johnson, tailored to the AR/VR Developer role: Mary Johnson Contact
Before: Information:
Address: 123 Main St, Anytown, USA 12345
Phone: (555) 555-5555
Email: mary.johnson@email.com
Professional Summary:
Highly motivated and experienced AR/VR Developer with expertise in Unity, C#,
summary:
highly motivated and detail-oriented product manager with 3+ years of experience in creating and executing successful product strategies.
Prompt: Role: data engineer; Resume: gina mehtadata engineer candidate gina mehta is a highly skilled and experienced data engineer with
Before: over 5 years of experience in designing, developing, and deploying scalable data solutions. She has a strong background in cloud computing, database design, and data visualization.
Key skills:
Cloud platforms (AWS, Azure, Google Cloud)
Database management (MySQL, PostgreSQL, MongoDB)
Data modeling and query…
After: a strong background in designing, developing, and deploying scalable data solutions. she has a proven track record of delivering high-quality data products that meet the needs of clients across various industries.
key skills and achievements:
data engineering: demonstrated expertise in designing, developing…
The effective terms are inherited from the base model and the training data, which are not necessarily the same as this project's own license. Review both before redistributing.
