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qsolv-qwen2.5-coder-7b-lora-gsm8k
dainlieu/qsolv-qwen2.5-coder-7b-lora-gsm8k
qsolv-qwen2.5-coder-7b-lora-gsm8k is a machine learning model from dainlieu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
This repository contains a LoRA adapter fine-tuned on an execution-verified GSM8K Python-of-Thought dataset.
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Public
Updated Jan 10, 2026
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jan 10, 2026
- Updated
- Jan 10, 2026
- SHA
- e1bd6dba
Base models
Model card
From the Hugging Face model README
Q-Solv LoRA Adapter (Qwen2.5-Coder-7B) - GSM8K Python-of-Thought
This repository contains a LoRA adapter fine-tuned on an execution-verified GSM8K Python-of-Thought dataset.
Base Model
unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit
Training
- Method: QLoRA (4-bit) + LoRA
- Samples: 1738
- Epochs: 2
- GPU: RTX 4060 Ti 16GB
- Training framework: Unsloth + TRL SFTTrainer
- Loss masked to train only on assistant responses (chat SFT)
Inference (PEFT)
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
base_model = "unsloth/Qwen2.5-Coder-7B-Instruct-bnb-4bit"
adapter_id = "dainlieu/qsolv-qwen2.5-coder-7b-lora-gsm8k"
tokenizer = AutoTokenizer.from_pretrained(base_model)
model = AutoModelForCausalLM.from_pretrained(base_model, device_map="auto")
model = PeftModel.from_pretrained(model, adapter_id)
- License
- apache-2.0
- Created
- Jan 10, 2026
- Updated
- Jan 10, 2026