Comparison
bpemb vs hazm
Verdict
Pick bpemb if bpemb provides pre-trained subword embeddings using Byte-Pair Encoding for up to 275 languages, which can be beneficial in multi-lingual NLP tasks; pick hazm if hazm is a Persian NLP Toolkit used for dependency parsing, embeddings, lemmatization, normalization, POS tagging and tokenization in Python.
Markdown twin · bpemb alternatives · hazm alternatives
GraphCanon updated today
Trust & integrity
| Signal | bpemb | hazm |
|---|---|---|
| Maintenance | Dormant (690d since push) As of today · github_public_v1 | Slowing (142d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) 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 |
Tagline
- bpemb
- Pre-trained subword embeddings in 275 languages using Byte-Pair Encoding
- hazm
- Persian NLP Toolkit for dependency parsing, embeddings, lemmatization, normalization, POS tagging, and tokenization
Stars
- bpemb
- 1.2k
- hazm
- 1.4k
Forks
- bpemb
- 100
- hazm
- 208
Open issues
- bpemb
- 6
- hazm
- 8
Language
- bpemb
- Python
- hazm
- Python
Adopt for
- bpemb
- bpemb provides pre-trained subword embeddings using Byte-Pair Encoding for up to 275 languages, which can be beneficial in multi-lingual NLP tasks.
- hazm
- Hazm is a Persian NLP Toolkit used for dependency parsing, embeddings, lemmatization, normalization, POS tagging and tokenization in Python.
Persona
- bpemb
- -
- hazm
- -
Runtime
- bpemb
- -
- hazm
- -
License
- bpemb
- MIT License: Permissive free software license granting users freedom to use, modify, and distribute the software.
- hazm
- MIT
Last pushed
- bpemb
- Oct 1, 2024
- hazm
- Apr 1, 2026
Categories
- bpemb
- Data & Retrieval
- hazm
- Data & Retrieval, Model Training
Trust and health
Maintenance
- bpemb
- Dormant (18%)
- hazm
- Slowing (36%)
Days since push
- bpemb
- 690d
- hazm
- 142d
Open issues (now)
- bpemb
- 6
- hazm
- 8
Stars delta
- bpemb
- +2 (30d)
- hazm
- +5 (30d)
Open issues delta
- bpemb
- 0 (30d)
- hazm
- +1 (30d)
Owner type
- bpemb
- User
- hazm
- Organization
Full report
- bpemb
- Trust report
- hazm
- Trust report
Shared compatibility
- Python · bpemb: Python runtime · hazm: Python runtime
Choose bpemb if…
- Requirements: Requires Python environment to operate effectively across various multilingual applications.
- Tags unique to bpemb: multilingual, subword-embeddings.
- When working on multilingual projects that span a vast array of languages (up to 275) where language-specific data is sparse or unavailable
When NOT to use bpemb
- If your project focuses solely on high-resource languages like English, Spanish, French where more specialized models provide better performance per task
- When the task specifically requires character-level or word-level embeddings and not subword tokenization provided by Byte-Pair Encoding (BPE)
Choose hazm if…
- Tags unique to hazm: dependency-parser, lemmatization, normalization, persian-nlp.
- Also covers Model Training.
- When working exclusively with Farsi language texts where comprehensive processing tools like dependency parsing or POS tagging are required.
When NOT to use hazm
- If the project involves languages other than Persian, as Hazm lacks capabilities for multilingual support beyond Farsi.
- When advanced machine learning models requiring extensive training data and resources are necessary; Hazm provides utilities but does not include state-of-the-art models.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (bheinzerling/bpemb) · observed Aug 22, 2026
- GitHub forks (bheinzerling/bpemb) · observed Aug 22, 2026
- Last push (bheinzerling/bpemb) · observed Oct 1, 2024
- License file (MIT) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (roshan-research/hazm) · observed Aug 22, 2026
- GitHub forks (roshan-research/hazm) · observed Aug 22, 2026
- Last push (roshan-research/hazm) · observed Apr 1, 2026
- License file (MIT) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: bpemb 1.2k · hazm 1.4k (synced Aug 22, 2026).
Common questions
- What is the difference between bpemb and hazm?
- bpemb: Pre-trained subword embeddings in 275 languages using Byte-Pair Encoding. hazm: Persian NLP Toolkit for dependency parsing, embeddings, lemmatization, normalization, POS tagging, and tokenization. See the comparison table for live GitHub stats and shared categories.
- When should I choose bpemb over hazm?
- Choose bpemb over hazm when Requirements: Requires Python environment to operate effectively across various multilingual applications; Tags unique to bpemb: multilingual, subword-embeddings; When working on multilingual projects that span a vast array of languages (up to 275) where language-specific data is sparse or unavailable.
- When should I choose hazm over bpemb?
- Choose hazm over bpemb when Tags unique to hazm: dependency-parser, lemmatization, normalization, persian-nlp; Also covers Model Training; When working exclusively with Farsi language texts where comprehensive processing tools like dependency parsing or POS tagging are required.
- When should I avoid bpemb?
- If your project focuses solely on high-resource languages like English, Spanish, French where more specialized models provide better performance per task When the task specifically requires character-level or word-level embeddings and not subword tokenization provided by Byte-Pair Encoding (BPE)
- When should I avoid hazm?
- If the project involves languages other than Persian, as Hazm lacks capabilities for multilingual support beyond Farsi. When advanced machine learning models requiring extensive training data and resources are necessary; Hazm provides utilities but does not include state-of-the-art models.
- Is bpemb or hazm more popular on GitHub?
- hazm has more GitHub stars (1,417 vs 1,224). Stars measure visibility, not whether either tool fits your constraints.
- Are bpemb and hazm open source?
- Yes - both are open-source projects on GitHub (bpemb: MIT, hazm: MIT).
- Where can I find alternatives to bpemb or hazm?
- GraphCanon lists graph-backed alternatives at bpemb alternatives and hazm alternatives (bpemb markdown twin, hazm 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, bpemb or hazm?
- bpemb: Dormant. hazm: Slowing. 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 bpemb and hazm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: bpemb trust report; hazm trust report.