Instructions to use ethicalabs/Flwr-Qwen2.5-7B-Instruct-Coding-PEFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ethicalabs/Flwr-Qwen2.5-7B-Instruct-Coding-PEFT with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "ethicalabs/Flwr-Qwen2.5-7B-Instruct-Coding-PEFT") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
datasets:
- flwrlabs/code-alpaca-20k
language:
- en
base_model:
- Qwen/Qwen2.5-7B-Instruct
pipeline_tag: text-generation
library_name: peft
tags:
- text-generation-inference
- code
Model Details
This PEFT adapter has been trained by using Flower, a friendly federated AI framework.
The adapter and benchmark results have been submitted to the FlowerTune LLM Code Leaderboard.
Please check the following GitHub project for details on how to reproduce training and evaluation steps: