--- title: "stock-rnn vs stanford_alpaca" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lilianweng-stock-rnn-vs-tatsu-lab-stanford-alpaca" tools: ["lilianweng-stock-rnn", "tatsu-lab-stanford-alpaca"] --- # stock-rnn vs stanford_alpaca *GraphCanon updated Jul 11, 2026* ## Verdict Pick stock-rnn when tags unique to stock-rnn: embeddings, lstm, rnn-tensorflow, stock-price-prediction; pick stanford_alpaca when tags unique to stanford_alpaca: deep-learning, instruction-following, language-model. [stock-rnn](https://lilianweng.github.io/lil-log) reports 2.0k GitHub stars, 673 forks, and 24 open issues, last pushed Jul 28, 2022. [stanford_alpaca](https://crfm.stanford.edu/2023/03/13/alpaca.html) has 30k stars, 4.0k forks, and 188 open issues, last pushed Jul 17, 2024. Figures are from public GitHub metadata via [stock-rnn's repository](https://github.com/lilianweng/stock-rnn) and [stanford_alpaca's repository](https://github.com/tatsu-lab/stanford_alpaca). | | [stock-rnn](/tools/lilianweng-stock-rnn.md) | [stanford_alpaca](/tools/tatsu-lab-stanford-alpaca.md) | | --- | --- | --- | | Tagline | Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings. | Code and documentation to train Stanford's Alpaca models, and generate the data. | | Stars | 1,976 | 30,250 | | Forks | 673 | 3,985 | | Open issues | 24 | 188 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Model Training, Vector Databases | LLM Frameworks, Model Training, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [stock-rnn](/tools/lilianweng-stock-rnn.md) | [stanford_alpaca](/tools/tatsu-lab-stanford-alpaca.md) | | --- | --- | --- | | Days since push | 1444d | 724d | | Open issues (now) | 24 | 188 | | Owner type | User | Organization | | Security scan | No lockfile | 46 low (46 low) | | Full report | [trust report](/tools/lilianweng-stock-rnn/trust.md) | [trust report](/tools/tatsu-lab-stanford-alpaca/trust.md) | ## Choose when ### Choose stock-rnn if… - Tags unique to stock-rnn: embeddings, lstm, rnn-tensorflow, stock-price-prediction. - Leaner open-issue backlog (24). ### Choose stanford_alpaca if… - Tags unique to stanford_alpaca: deep-learning, instruction-following, language-model. - Also covers LLM Frameworks. - More GitHub stars (30k vs 2.0k) - visibility, not fit. ## When NOT to use stock-rnn - Last GitHub push was 1445 days ago (dormant maintenance, Jul 28, 2022). Validate activity before betting a new project on stock-rnn. - 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 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. ## Common questions ### What is the difference between stock-rnn and stanford_alpaca? stock-rnn: Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.. stanford_alpaca: Code and documentation to train Stanford's Alpaca models, and generate the data.. See the comparison table for live GitHub stats and shared categories. ### When should I choose stock-rnn over stanford_alpaca? Choose stock-rnn over stanford_alpaca when Tags unique to stock-rnn: embeddings, lstm, rnn-tensorflow, stock-price-prediction; Leaner open-issue backlog (24). ### When should I choose stanford_alpaca over stock-rnn? Choose stanford_alpaca over stock-rnn when Tags unique to stanford_alpaca: deep-learning, instruction-following, language-model; Also covers LLM Frameworks; More GitHub stars (30k vs 2.0k) - visibility, not fit. ### When should I avoid stock-rnn? Last GitHub push was 1445 days ago (dormant maintenance, Jul 28, 2022). Validate activity before betting a new project on stock-rnn. 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 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. ### Is stock-rnn or stanford_alpaca more popular on GitHub? stanford_alpaca has more GitHub stars (30,250 vs 1,976). Stars measure visibility, not whether either tool fits your constraints. ### Are stock-rnn and stanford_alpaca open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to stock-rnn or stanford_alpaca? GraphCanon lists graph-backed alternatives at [stock-rnn alternatives](/tools/lilianweng-stock-rnn/alternatives) and [stanford_alpaca alternatives](/tools/tatsu-lab-stanford-alpaca/alternatives) ([stock-rnn markdown twin](/tools/lilianweng-stock-rnn/alternatives.md), [stanford_alpaca markdown twin](/tools/tatsu-lab-stanford-alpaca/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/lilianweng-stock-rnn-vs-tatsu-lab-stanford-alpaca.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, stock-rnn or stanford_alpaca? stock-rnn: Dormant. stanford_alpaca: 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 stock-rnn and stanford_alpaca? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [stock-rnn trust report](/tools/lilianweng-stock-rnn/trust); [stanford_alpaca trust report](/tools/tatsu-lab-stanford-alpaca/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lilianweng-stock-rnn`](/api/graphcanon/graph?tool=lilianweng-stock-rnn) - 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/_