Instructions to use akshayrinku/tinyllama-resume-tailor-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use akshayrinku/tinyllama-resume-tailor-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "akshayrinku/tinyllama-resume-tailor-lora") - Notebooks
- Google Colab
- Kaggle
TinyLlama Resume Tailor β Fine-Tuned with LoRA
A fine-tuned version of TinyLlama-1.1B-Chat that automatically tailors resumes to match specific job descriptions. Built using LoRA (Low-Rank Adaptation) for parameter-efficient fine-tuning.
What It Does
Input: A job description + a base resume Output: A tailored, ATS-optimized resume that:
- Reorders skills by relevance to the JD
- Emphasizes matching experience
- Aligns keywords with role requirements
- Maintains factual accuracy from the original resume
Model Details
- Developed by: Akshay Pillalamarri
- Model type: Causal Language Model (Fine-tuned with LoRA)
- Language: English
- License: MIT
- Base model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
Training Details
- Method: LoRA via PEFT library
- Trainable params: ~1% of base model
- Target modules: q_proj, k_proj, v_proj, o_proj
- Rank (r): 16, Alpha: 32, Dropout: 0.05
- Epochs: 3
- Batch size: 2 with gradient accumulation of 4
- Learning rate: 2e-4
- Hardware: Google Colab T4 GPU
- Dataset: Custom dataset of resume-JD pairs across multiple roles
How to Use
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
base_model = AutoModelForCausalLM.from_pretrained(
"TinyLlama/TinyLlama-1.1B-Chat-v1.0",
torch_dtype=torch.float16,
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0")
model = PeftModel.from_pretrained(base_model, "akshayrinku/tinyllama-resume-tailor-lora")
Limitations
- Trained on a small dataset for demonstration purposes
- May produce hallucinated content; always review output
- English language only
- Optimized for tech roles
About the Author
I'm Akshay Pillalamarri β AI/ML Engineer and Software Developer based in Folsom, CA. MS in Computer Science from University of Central Missouri.
- GitHub: github.com/akshaypillalamarri
- LinkedIn: linkedin.com/in/akshay-pillalamarri
- Portfolio: akshaypillalamarri.github.io
Currently open to AI/ML Engineering, SDET, and Software Development roles.
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Model tree for akshayrinku/tinyllama-resume-tailor-lora
Base model
TinyLlama/TinyLlama-1.1B-Chat-v1.0