AutoCoder: Enhancing Code Large Language Model with
  AIEV-Instruct
We introduce AutoCoder, the first Large Language Model to surpass GPT-4 Turbo
(April 2024) and GPT-4o in pass@1 on the Human Eval benchmark test
(90.9% vs. 90.2%). In addition, AutoCoder offers a more
versatile code interpreter compared to GPT-4 Turbo and GPT-4o. It's code
interpreter can install external packages instead of limiting to built-in
packages. AutoCoder's training data is a multi-turn dialogue dataset created by
a system combining agent interaction and external code execution verification,
a method we term \textsc{AIEV-Instruct} (Instruction Tuning with
Agent-Interaction and Execution-Verified). Compared to previous large-scale
code dataset generation methods, AIEV-Instruct reduces dependence on
proprietary large models and provides execution-validated code dataset. The
code and the demo video is available in
https://github.com/bin123apple/AutoCoder.
6653eaa9fda461267c7aa31b
Bin Lei
claimed_verified
2024-05-27T19:46:15.466Z
648a2042e8bee533291da413
/avatars/83b918ddd7e2130a1c72ae74606068dc.svg
Bin Lei
user
Bin12345
6653eaa9fda461267c7aa31c
Yuchen Li
6653eaa9fda461267c7aa31d
Qiuwu Chen
admin_assigned
2024-05-27T10:03:48.246Z
63ae84873e98f3ec1945d09d
/avatars/26c6cf2c824ec777c55e56947809d7c7.svg
qiuwuchen
user
qiuwu
AutoCoder: Enhancing Code Large Language Model with
  AIEV-Instruct
We introduce AutoCoder, the first Large Language Model to surpass GPT-4 Turbo
(April 2024) and GPT-4o in pass@1 on the Human Eval benchmark test
(90.9% vs. 90.2%). In addition, AutoCoder offers a more
versatile code interpreter compared to GPT-4 Turbo and GPT-4o. It's code
interpreter can install external packages instead of limiting to built-in
packages. AutoCoder's training data is a multi-turn dialogue dataset created by
a system combining agent interaction and external code execution verification,
a method we term \textsc{AIEV-Instruct} (Instruction Tuning with
Agent-Interaction and Execution-Verified). Compared to previous large-scale
code dataset generation methods, AIEV-Instruct reduces dependence on
proprietary large models and provides execution-validated code dataset. The
code and the demo video is available in
https://github.com/bin123apple/AutoCoder.
AutoCoder, a Large Language Model surpassing GPT-4 Turbo and GPT-4o, uses a novel training method \textsc{AIEV-Instruct} to enhance code interpretation and execution validation.
Large Language Model GPT-4 Turbo GPT-4o Human Eval benchmark pass@1 code interpreter external packages multi-turn dialogue dataset AIEV-Instruct Instruction Tuning Agent-Interaction Execution-Verified