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Comparison

CodeBERT vs lever

Verdict

Pick CodeBERT if codeBERT is an advanced pre-trained model for programming and natural language tasks in multiple languages like Python and Java; pick lever if lever offers support for verifying language-to-code generation through actual code execution.

Markdown twin · CodeBERT alternatives · lever alternatives

GraphCanon updated 2w

CodeBERT logo

CodeBERT

microsoft/CodeBERT

★ 2.8kpushed Jul 9, 2023
vs
lever logo

lever

niansong1996/lever

★ 90pushed Jul 5, 2023

Trust & integrity

SignalCodeBERTlever
Maintenance
Dormant (1123d since push)
As of 2w · github_public_v1
Dormant (1127d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Personal account
As of 2w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No published findings from this source as of 2026-07-11
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1
CodeBERT trust reportlever trust reportTrust methodology

Tagline

CodeBERT
CodeBERT series models for code pretraining in Python and programming languages
lever
Supports learning to verify language-to-code generation with execution

Stars

CodeBERT
2.8k
lever
90

Forks

CodeBERT
497
lever
8

Open issues

CodeBERT
86
lever
2

Language

CodeBERT
Python
lever
Python

Adopt for

CodeBERT
CodeBERT is an advanced pre-trained model for programming and natural language tasks in multiple languages like Python and Java.
lever
Lever offers support for verifying language-to-code generation through actual code execution.

Persona

CodeBERT
-
lever
-

Runtime

CodeBERT
-
lever
-

License

CodeBERT
MIT
lever
Lever's source code is freely available under an MIT License for modification and distribution in both personal and commercial projects.

Last pushed

CodeBERT
Jul 9, 2023
lever
Jul 5, 2023

Categories

CodeBERT
Model Training
lever
Evaluation & Observability, Model Training

Trust and health

Days since push

CodeBERT
1123d
lever
1127d

Open issues (now)

CodeBERT
86
lever
2

Owner type

CodeBERT
Organization
lever
User

OSV dependency advisories

CodeBERT
No lockfile (source not queried)
lever
No published findings from this source as of 2026-07-11

Full report

CodeBERT
Trust report
lever
Trust report

Shared compatibility

  • Python · CodeBERT: Python runtime · lever: Python runtime

Choose CodeBERT if…

  • Requirements: Install torch and transformers via pip before using CodeBERT for embedding generation or other tasks; Ensure Python and Hugging Face's transformers framework are available, as they form the core execution environment for utilizing this model.
  • Tags unique to CodeBERT: code pretraining, transformers framework.
  • When you need to work on tasks involving both programming and natural language processing across six different programming languages: Python, Java, JavaScript, PHP, Ruby, Go

When NOT to use CodeBERT

  • Avoid for direct mask prediction tasks without MLM (Masked Language Model) fine-tuning as CodeBERT is not natively equipped for such tasks unlike its variant designed with MLM capabilities
  • Do not consider it if your project requires pre-training models on a wider variety of programming languages beyond the six supported by this model
GitHubDetails

Choose lever if…

  • Requirements: All of the pipelines have been tested on Linux machines only, requiring possibly custom `tree-sitter` parsers for other platforms..
  • Tags unique to lever: code verification, execution based verification, language-to-code.
  • Also covers Evaluation & Observability.
  • When the development team needs to verify accuracy of generated code from language inputs based on execution, and has access to Linux machines to ensure seamless functionality.

When NOT to use lever

  • Avoid Lever if developing in an environment other than Linux as it requires the use of tree-sitter parsers, which may not be compatible with your system.
  • Do not choose Lever if you seek a tool that does not require setting up a conda environment and installing specific dependencies to operate.
GitHubDetails

Explore

CodeBERT trust report →lever trust report →Model Training category →Evaluation & Observability category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: CodeBERT 2.8k · lever 90 (synced Aug 5, 2026).

Common questions

What is the difference between CodeBERT and lever?
CodeBERT: CodeBERT series models for code pretraining in Python and programming languages. lever: Supports learning to verify language-to-code generation with execution. See the comparison table for live GitHub stats and shared categories.
When should I choose CodeBERT over lever?
Choose CodeBERT over lever when Requirements: Install torch and transformers via pip before using CodeBERT for embedding generation or other tasks; Ensure Python and Hugging Face's transformers framework are available, as they form the core execution environment for utilizing this model; Tags unique to CodeBERT: code pretraining, transformers framework; When you need to work on tasks involving both programming and natural language processing across six different programming languages: Python, Java, JavaScript, PHP, Ruby, Go.
When should I choose lever over CodeBERT?
Choose lever over CodeBERT when Requirements: All of the pipelines have been tested on Linux machines only, requiring possibly custom tree-sitter parsers for other platforms.; Tags unique to lever: code verification, execution based verification, language-to-code; Also covers Evaluation & Observability; When the development team needs to verify accuracy of generated code from language inputs based on execution, and has access to Linux machines to ensure seamless functionality.
When should I avoid CodeBERT?
Avoid for direct mask prediction tasks without MLM (Masked Language Model) fine-tuning as CodeBERT is not natively equipped for such tasks unlike its variant designed with MLM capabilities Do not consider it if your project requires pre-training models on a wider variety of programming languages beyond the six supported by this model
When should I avoid lever?
Avoid Lever if developing in an environment other than Linux as it requires the use of tree-sitter parsers, which may not be compatible with your system. Do not choose Lever if you seek a tool that does not require setting up a conda environment and installing specific dependencies to operate.
Is CodeBERT or lever more popular on GitHub?
CodeBERT has more GitHub stars (2,787 vs 90). Stars measure visibility, not whether either tool fits your constraints.
Are CodeBERT and lever open source?
Yes - both are open-source projects on GitHub (CodeBERT: MIT, lever: MIT).
Where can I find alternatives to CodeBERT or lever?
GraphCanon lists graph-backed alternatives at CodeBERT alternatives and lever alternatives (CodeBERT markdown twin, lever markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, CodeBERT or lever?
CodeBERT: Dormant. lever: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for CodeBERT and lever?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: CodeBERT trust report; lever trust report.

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