Comparison
llm-lobbyist vs llm-course
Verdict
Pick llm-lobbyist when tags unique to llm-lobbyist: jupyter notebook; pick llm-course when requirements: Course materials are available in Colab notebooks; access requires a Google account.
Markdown twin · llm-lobbyist alternatives · llm-course alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | llm-lobbyist | llm-course |
|---|---|---|
| Maintenance | Dormant (1275d since push) As of today · github_public_v1 | Slowing (155d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- llm-lobbyist
- Code for the paper: "Large Language Models as Corporate Lobbyists" (2023).
- llm-course
- Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Stars
- llm-lobbyist
- 174
- llm-course
- 81k
Forks
- llm-lobbyist
- 14
- llm-course
- 9.4k
Open issues
- llm-lobbyist
- 0
- llm-course
- 84
Language
- llm-lobbyist
- Jupyter Notebook
- llm-course
- -
Adopt for
- llm-lobbyist
- -
- llm-course
- The llm-course provides a comprehensive guided course on Large Language Models (LLMs), divided into three parts: LLM Fundamentals, The LLM Scientist, and The LLM Engineer. It includes resources such as Colab notebooks to
Persona
- llm-lobbyist
- -
- llm-course
- -
Runtime
- llm-lobbyist
- -
- llm-course
- -
License
- llm-lobbyist
- -
- llm-course
- Apache-2.0
Last pushed
- llm-lobbyist
- Jan 13, 2023
- llm-course
- Feb 5, 2026
Categories
- llm-lobbyist
- Vector Databases, LLM Frameworks, Evaluation & Observability
- llm-course
- LLM Frameworks, Model Training, Evaluation & Observability, Inference & Serving
Trust and health
Maintenance
- llm-lobbyist
- Dormant (18%)
- llm-course
- Slowing (36%)
Days since push
- llm-lobbyist
- 1275d
- llm-course
- 155d
Open issues (now)
- llm-lobbyist
- 0
- llm-course
- 84
Full report
- llm-lobbyist
- Trust report
- llm-course
- Trust report
Choose llm-lobbyist if…
- Tags unique to llm-lobbyist: jupyter notebook.
- Also covers Vector Databases.
- Leaner open-issue backlog (0).
When NOT to use llm-lobbyist
- Last GitHub push was 1276 days ago (dormant maintenance, Jan 13, 2023). Validate activity before betting a new project on llm-lobbyist.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Choose llm-course if…
- Requirements: Course materials are available in Colab notebooks; access requires a Google account.
- Tags unique to llm-course: colab-notebooks, machine-learning, course, large-language-models.
- Also covers Model Training, Inference & Serving.
- - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge
When NOT to use llm-course
- - If you only require a quick introduction to LLMs without deep dive into core components
- - When you prefer working directly with commercial platforms that provide complete services rather than following detailed steps on building and deploying models yourself through this course's open,DI
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (JohnNay/llm-lobbyist) · observed Jul 11, 2026
- GitHub forks (JohnNay/llm-lobbyist) · observed Jul 11, 2026
- Last push (JohnNay/llm-lobbyist) · observed Jan 13, 2023
- License file (unknown) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (mlabonne/llm-course) · observed Jul 11, 2026
- GitHub forks (mlabonne/llm-course) · observed Jul 11, 2026
- Last push (mlabonne/llm-course) · observed Feb 5, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: llm-lobbyist 174 · llm-course 81k (synced Jul 11, 2026).
Common questions
- What is the difference between llm-lobbyist and llm-course?
- llm-lobbyist: Code for the paper: "Large Language Models as Corporate Lobbyists" (2023).. llm-course: Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.. See the comparison table for live GitHub stats and shared categories.
- When should I choose llm-lobbyist over llm-course?
- Choose llm-lobbyist over llm-course when Tags unique to llm-lobbyist: jupyter notebook; Also covers Vector Databases; Leaner open-issue backlog (0).
- When should I choose llm-course over llm-lobbyist?
- Choose llm-course over llm-lobbyist when Requirements: Course materials are available in Colab notebooks; access requires a Google account; Tags unique to llm-course: colab-notebooks, machine-learning, course, large-language-models; Also covers Model Training, Inference & Serving; - When you want a comprehensive roadmap for understanding large language models including fundamental knowledge.
- When should I avoid llm-lobbyist?
- Last GitHub push was 1276 days ago (dormant maintenance, Jan 13, 2023). Validate activity before betting a new project on llm-lobbyist. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- When should I avoid llm-course?
- - If you only require a quick introduction to LLMs without deep dive into core components - When you prefer working directly with commercial platforms that provide complete services rather than following detailed steps on building and deploying models yourself through this course's open,DI
- Is llm-lobbyist or llm-course more popular on GitHub?
- llm-course has more GitHub stars (80,839 vs 174). Stars measure visibility, not whether either tool fits your constraints.
- Are llm-lobbyist and llm-course open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to llm-lobbyist or llm-course?
- GraphCanon lists graph-backed alternatives at llm-lobbyist alternatives and llm-course alternatives (llm-lobbyist markdown twin, llm-course 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, llm-lobbyist or llm-course?
- llm-lobbyist: Dormant. llm-course: 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 llm-lobbyist and llm-course?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: llm-lobbyist trust report; llm-course trust report.