# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("GoCodeo/TestCodeo")
model = AutoModelForCausalLM.from_pretrained("GoCodeo/TestCodeo")Quick Links
TestCodeo - GoCodeo's fine-tuned Language Model dedicated to Python unit test generation.
Approach
Our team curated a unique dataset of 200,000 prompt-completion pairs in alpaca format, specifically designed for Python unit test generation.
Two-Stage Finetuning Process
Stage 1: We fine-tuned the base Codellama 7B Python model with 25k easy and 75k medium instructions.
Stage 2: The resulting Test-Codeo-Base was further refined with the remaining medium-hard questions to develop TestCodeo.
Evaluation Methodology
Utilizing OpenAI's human eval dataset, we generated test cases for 164 coding instructions and measured code coverage.
Results
TestCodeo achieved an impressive 89% code coverage, surpassing Codellama's 17% and approaching GPT-3.5-turbo's 93%.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GoCodeo/TestCodeo")