---
title: "stanford_alpaca vs uniem"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/tatsu-lab-stanford-alpaca-vs-wangyuxinwhy-uniem"
tools: ["tatsu-lab-stanford-alpaca", "wangyuxinwhy-uniem"]
---

# stanford_alpaca vs uniem

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick stanford_alpaca when tags unique to stanford_alpaca: deep-learning, instruction-following, language-model; pick uniem when tags unique to uniem: embeddings, huggingface, nlp, sentence-embeddings.

[stanford_alpaca](https://crfm.stanford.edu/2023/03/13/alpaca.html) reports 30k GitHub stars, 4.0k forks, and 188 open issues, last pushed Jul 17, 2024. [uniem](https://github.com/wangyuxinwhy/uniem) has 876 stars, 72 forks, and 47 open issues, last pushed Sep 1, 2023. Figures are from public GitHub metadata via [stanford_alpaca's repository](https://github.com/tatsu-lab/stanford_alpaca) and [uniem's repository](https://github.com/wangyuxinwhy/uniem).

| | [stanford_alpaca](/tools/tatsu-lab-stanford-alpaca.md) | [uniem](/tools/wangyuxinwhy-uniem.md) |
| --- | --- | --- |
| Tagline | Code and documentation to train Stanford's Alpaca models, and generate the data. | unified embedding model |
| Stars | 30,250 | 876 |
| Forks | 3,985 | 72 |
| Open issues | 188 | 47 |
| Language | Python | Python |
| Adopt for | - | - |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 | Apache-2.0 |
| Categories | LLM Frameworks, Model Training, Vector Databases | Model Training, Vector Databases |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [stanford_alpaca](/tools/tatsu-lab-stanford-alpaca.md) | [uniem](/tools/wangyuxinwhy-uniem.md) |
| --- | --- | --- |
| Days since push | 724d | 1043d |
| Open issues (now) | 188 | 47 |
| Owner type | Organization | User |
| Security scan | 46 low (46 low) | No lockfile |
| Full report | [trust report](/tools/tatsu-lab-stanford-alpaca/trust.md) | [trust report](/tools/wangyuxinwhy-uniem/trust.md) |

## Choose when

### Choose stanford_alpaca if…

- Tags unique to stanford_alpaca: deep-learning, instruction-following, language-model.
- Also covers LLM Frameworks.
- More GitHub stars (30k vs 876) - visibility, not fit.

### Choose uniem if…

- Tags unique to uniem: embeddings, huggingface, nlp, sentence-embeddings.
- Leaner open-issue backlog (47).

## When NOT to use stanford_alpaca

- Last GitHub push was 725 days ago (dormant maintenance, Jul 17, 2024). Validate activity before betting a new project on stanford_alpaca.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

## When NOT to use uniem

- Last GitHub push was 1045 days ago (dormant maintenance, Sep 1, 2023). Validate activity before betting a new project on uniem.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

## Common questions

### What is the difference between stanford_alpaca and uniem?

stanford_alpaca: Code and documentation to train Stanford's Alpaca models, and generate the data.. uniem: unified embedding model. See the comparison table for live GitHub stats and shared categories.

### When should I choose stanford_alpaca over uniem?

Choose stanford_alpaca over uniem when Tags unique to stanford_alpaca: deep-learning, instruction-following, language-model; Also covers LLM Frameworks; More GitHub stars (30k vs 876) - visibility, not fit.

### When should I choose uniem over stanford_alpaca?

Choose uniem over stanford_alpaca when Tags unique to uniem: embeddings, huggingface, nlp, sentence-embeddings; Leaner open-issue backlog (47).

### When should I avoid stanford_alpaca?

Last GitHub push was 725 days ago (dormant maintenance, Jul 17, 2024). Validate activity before betting a new project on stanford_alpaca. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

### When should I avoid uniem?

Last GitHub push was 1045 days ago (dormant maintenance, Sep 1, 2023). Validate activity before betting a new project on uniem. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

### Is stanford_alpaca or uniem more popular on GitHub?

stanford_alpaca has more GitHub stars (30,250 vs 876). Stars measure visibility, not whether either tool fits your constraints.

### Are stanford_alpaca and uniem open source?

Yes - both are open-source projects on GitHub (stanford_alpaca: Apache-2.0, uniem: Apache-2.0).

### Where can I find alternatives to stanford_alpaca or uniem?

GraphCanon lists graph-backed alternatives at [stanford_alpaca alternatives](/tools/tatsu-lab-stanford-alpaca/alternatives) and [uniem alternatives](/tools/wangyuxinwhy-uniem/alternatives) ([stanford_alpaca markdown twin](/tools/tatsu-lab-stanford-alpaca/alternatives.md), [uniem markdown twin](/tools/wangyuxinwhy-uniem/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/tatsu-lab-stanford-alpaca-vs-wangyuxinwhy-uniem.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, stanford_alpaca or uniem?

stanford_alpaca: Dormant. uniem: 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 stanford_alpaca and uniem?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [stanford_alpaca trust report](/tools/tatsu-lab-stanford-alpaca/trust); [uniem trust report](/tools/wangyuxinwhy-uniem/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=tatsu-lab-stanford-alpaca`](/api/graphcanon/graph?tool=tatsu-lab-stanford-alpaca)
- 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/_
