GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
51views this month
Decision brief
CodeGeeX is an open-source multilingual code generation model that supports both Mindspore and PyTorch frameworks, making it suitable for developers working with Ascend 910 AI Processors or GPU platforms.
Good fit when
- When you need a multilingual code generation model that supports both Mindspore and PyTorch frameworks, allowing flexibility between Ascend 910 AI Processors and GPU platforms.
- If your project requires an open-source solution under the Apache-2.0 license, ensuring freedom to use, modify, and distribute the code.
Avoid when
- If your project is strictly limited to TensorFlow or other frameworks not supported by CodeGeeX, as it primarily supports Mindspore and PyTorch.
- When your development environment does not support Python 3.7+, CUDA 11+, PyTorch 1.10+, or DeepSpeed 0.6+, as these are the minimum requirements for running CodeGeeX.
- Requirements:
- Requires Docker; Requires Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+.; Supports installation via pip or through a Docker container for quick setup.
Observed Sep 18, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (766d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- 94 low (94 low)
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install CodeGeeXSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
CodeGeeX is an open-source multilingual code generation model initially implemented in Mindspore and trained on Ascend 910 AI Processors. It offers a torch-compatible version for GPU platforms.
Capability facts
- Languages
- python
Source: github.language · Sep 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 18, 2026)
Python 3.7+ / CUDA 11+ / PyTorch 1.10+ / DeepSpeed 0.6+ are required. Install ``codegeex``Source link
Tags
README
Getting Started CodeGeeX is initially implemented in Mindspore and trained Ascend 910 AI Processors. We provide a torch compatible version based on Megatron LM to facilitate usage on GPU platforms. Installation Python 3.7+ / CUDA 11+ / PyTorch 1.10+ / DeepSpeed 0.6+ are required....
For agents
This page has a .md twin and JSON over the API.