--- title: "awesome-embedding-models vs what_are_embeddings" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hironsan-awesome-embedding-models-vs-veekaybee-what-are-embeddings" tools: ["hironsan-awesome-embedding-models", "veekaybee-what-are-embeddings"] --- # awesome-embedding-models vs what_are_embeddings *GraphCanon updated Aug 22, 2026* ## Verdict Pick awesome-embedding-models if curated resources on embedding models for AI applications; pick what_are_embeddings if focuses on educational materials for understanding embeddings in ML and NLP using Jupyter Notebooks. [awesome-embedding-models](https://github.com/Hironsan/awesome-embedding-models) reports 1.9k GitHub stars, 249 forks, and 3 open issues, last pushed Apr 7, 2019. [what_are_embeddings](http://vickiboykis.com/what_are_embeddings/) has 1.1k stars, 86 forks, and 0 open issues, last pushed Jan 17, 2026. Figures are from public GitHub metadata via [awesome-embedding-models's repository](https://github.com/Hironsan/awesome-embedding-models) and [what_are_embeddings's repository](https://github.com/veekaybee/what_are_embeddings). | | [awesome-embedding-models](/tools/hironsan-awesome-embedding-models.md) | [what_are_embeddings](/tools/veekaybee-what-are-embeddings.md) | | --- | --- | --- | | Tagline | A curated list of embedding models tutorials, projects and communities. | A deep dive into embeddings starting from fundamentals | | Stars | 1,850 | 1,096 | | Forks | 249 | 86 | | Open issues | 3 | 0 | | Language | Jupyter Notebook | Jupyter Notebook | | Adopt for | Curated resources on embedding models for AI applications | Focuses on educational materials for understanding embeddings in ML and NLP using Jupyter Notebooks. | | Persona | - | - | | Runtime | - | - | | License | MIT | - | | Categories | Data & Retrieval, Model Training | Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-embedding-models](/tools/hironsan-awesome-embedding-models.md) | [what_are_embeddings](/tools/veekaybee-what-are-embeddings.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 2693d | 217d | | Open issues (now) | 3 | 0 | | Stars delta | +5 (30d) | +4 (30d) | | Full report | [trust report](/tools/hironsan-awesome-embedding-models/trust.md) | [trust report](/tools/veekaybee-what-are-embeddings/trust.md) | ## Decision facts: awesome-embedding-models - **Adopt for:** Curated resources on embedding models for AI applications ## Decision facts: what_are_embeddings - **Adopt for:** Focuses on educational materials for understanding embeddings in ML and NLP using Jupyter Notebooks. ## Choose when ### Choose awesome-embedding-models if… - Tags unique to awesome-embedding-models: embedding-models, machine-learning, natural-language-processing, papers. - Also covers Model Training. - Need a variety of tutorials and projects focused specifically on embedding models ### Choose what_are_embeddings if… - Tags unique to what_are_embeddings: machine-learning-algorithms, nlp-machine-learning. - When you are looking to gain foundational knowledge about how embeddings work in machine learning and natural language processing tasks. - More recently updated (last pushed Jan 17, 2026). ## When NOT to use awesome-embedding-models - Looking for a tool that provides direct model training capabilities instead of resources - Seeking detailed code implementations rather than a curated list of existing work ## When NOT to use what_are_embeddings - If you need practical, real-world application examples or code implementations not grounded in explanatory educational content. - When an advanced understanding of embeddings is required as this repository prioritizes fundamental comprehension over deep technical insights. ## Common questions ### What is the difference between awesome-embedding-models and what_are_embeddings? awesome-embedding-models: A curated list of embedding models tutorials, projects and communities.. what_are_embeddings: A deep dive into embeddings starting from fundamentals. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-embedding-models over what_are_embeddings? Choose awesome-embedding-models over what_are_embeddings when Tags unique to awesome-embedding-models: embedding-models, machine-learning, natural-language-processing, papers; Also covers Model Training; Need a variety of tutorials and projects focused specifically on embedding models. ### When should I choose what_are_embeddings over awesome-embedding-models? Choose what_are_embeddings over awesome-embedding-models when Tags unique to what_are_embeddings: machine-learning-algorithms, nlp-machine-learning; When you are looking to gain foundational knowledge about how embeddings work in machine learning and natural language processing tasks; More recently updated (last pushed Jan 17, 2026). ### When should I avoid awesome-embedding-models? Looking for a tool that provides direct model training capabilities instead of resources Seeking detailed code implementations rather than a curated list of existing work ### When should I avoid what_are_embeddings? If you need practical, real-world application examples or code implementations not grounded in explanatory educational content. When an advanced understanding of embeddings is required as this repository prioritizes fundamental comprehension over deep technical insights. ### Is awesome-embedding-models or what_are_embeddings more popular on GitHub? awesome-embedding-models has more GitHub stars (1,850 vs 1,096). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-embedding-models and what_are_embeddings open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to awesome-embedding-models or what_are_embeddings? GraphCanon lists graph-backed alternatives at [awesome-embedding-models alternatives](/tools/hironsan-awesome-embedding-models/alternatives) and [what_are_embeddings alternatives](/tools/veekaybee-what-are-embeddings/alternatives) ([awesome-embedding-models markdown twin](/tools/hironsan-awesome-embedding-models/alternatives.md), [what_are_embeddings markdown twin](/tools/veekaybee-what-are-embeddings/alternatives.md)), 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](/compare/hironsan-awesome-embedding-models-vs-veekaybee-what-are-embeddings.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-embedding-models or what_are_embeddings? awesome-embedding-models: Dormant. what_are_embeddings: 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 awesome-embedding-models and what_are_embeddings? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-embedding-models trust report](/tools/hironsan-awesome-embedding-models/trust); [what_are_embeddings trust report](/tools/veekaybee-what-are-embeddings/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hironsan-awesome-embedding-models`](/api/graphcanon/graph?tool=hironsan-awesome-embedding-models) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_