Xwin-LM/XwinCoder-34B

XwinCoder

We are glad to introduce our instruction finetuned code generation models based on CodeLLaMA: XwinCoder. We release model weights and evaluation code.

Repository: https://github.com/Xwin-LM/Xwin-LM/tree/main/Xwin-Coder

Models:

Model	🤗hf link	HumanEval pass@1	MBPP pass@1	APPS-intro pass@5
XwinCoder-7B	link	63.8	57.4	31.5
XwinCoder-13B	link	68.8	60.1	35.4
XwinCoder-34B	link	74.2	64.8	43.0

Updates

• 💥 We released XwinCoder-7B, XwinCoder-13B, XwinCoder-34B. Our XwinCoder-34B reached 74.2 on HumanEval and it achieves comparable performance as GPT-3.5-turbo on 6 benchmarks.

• We support evaluating instruction finetuned models on HumanEval, MBPP, APPS, DS1000 and MT-Bench. See our github repository.

Overview

• To fully demonstrate our model's coding capabilities in real-world usage scenarios, we have conducted thorough evaluations on several existing mainstream coding capability leaderboards (rather than only on the currently most popular HumanEval).
• As shown in the radar chart results, our 34B model achieves comparable performance as GPT-3.5-turbo on coding abilities.
• It is worth mentioning that, to ensure accurate visualization, our radar chart has not been scaled (only translated; MT-Bench score is scaled by 10x to be more comparable with other benchmarks).
• Multiple-E-avg6 refer to the 6 languages used in CodeLLaMA paper. Results of GPT-4 and GPT-3.5-turbo are conducted by us, more details will be released later.

Demo

We provide a chat demo in our github repository, here are some examples: