Comparison
awesome-llm-human-preference-datasets vs awesome-RLHF
Verdict
Pick awesome-llm-human-preference-datasets if awesome-llm-human-preference-datasets is an open-source repository that curates a collection of human preference datasets for fine-tuning large language models (LLMs), with a focus on reinforcement learning with human反馈被; pick awesome-RLHF if awesome-RLHF is a curated resource list focusing on reinforcement learning with human feedback (RLHF), which is crucial for refining large language models through interactive training methods.
Markdown twin · awesome-llm-human-preference-datasets alternatives · awesome-RLHF alternatives
GraphCanon updated 2d
awesome-llm-human-preference-datasets
glgh/awesome-llm-human-preference-datasets
★ 390pushed Oct 4, 2023
Trust & integrity
| Signal | awesome-llm-human-preference-datasets | awesome-RLHF |
|---|---|---|
| Maintenance | Dormant (1036d since push) As of 1w · github_public_v1 | Steady (89d since push) As of 2d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1w · github_public_v1 | Not a fork · Organization account As of 2d · 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
- awesome-llm-human-preference-datasets
- Curated list of Human Preference Datasets for LLM fine-tuning, RLHF, and eval
- awesome-RLHF
- A curated list of reinforcement learning with human feedback resources (continually updated)
Stars
- awesome-llm-human-preference-datasets
- 390
- awesome-RLHF
- 4.4k
Forks
- awesome-llm-human-preference-datasets
- 19
- awesome-RLHF
- 258
Open issues
- awesome-llm-human-preference-datasets
- 0
- awesome-RLHF
- 6
Language
- awesome-llm-human-preference-datasets
- -
- awesome-RLHF
- -
Adopt for
- awesome-llm-human-preference-datasets
- awesome-llm-human-preference-datasets is an open-source repository that curates a collection of human preference datasets for fine-tuning large language models (LLMs), with a focus on reinforcement learning with human反馈被
- awesome-RLHF
- awesome-RLHF is a curated resource list focusing on reinforcement learning with human feedback (RLHF), which is crucial for refining large language models through interactive training methods.
Persona
- awesome-llm-human-preference-datasets
- -
- awesome-RLHF
- -
Runtime
- awesome-llm-human-preference-datasets
- -
- awesome-RLHF
- -
License
- awesome-llm-human-preference-datasets
- MIT
- awesome-RLHF
- Apache-2.0
Last pushed
- awesome-llm-human-preference-datasets
- Oct 4, 2023
- awesome-RLHF
- May 20, 2026
Categories
- awesome-llm-human-preference-datasets
- Evaluation & Observability, Model Training
- awesome-RLHF
- Evaluation & Observability, Model Training
Trust and health
Maintenance
- awesome-llm-human-preference-datasets
- Dormant (18%)
- awesome-RLHF
- Steady (60%)
Days since push
- awesome-llm-human-preference-datasets
- 1036d
- awesome-RLHF
- 89d
Open issues (now)
- awesome-llm-human-preference-datasets
- 0
- awesome-RLHF
- 6
Stars delta
- awesome-llm-human-preference-datasets
- Unknown
- awesome-RLHF
- +9 (30d)
Open issues delta
- awesome-llm-human-preference-datasets
- Unknown
- awesome-RLHF
- 0 (30d)
Owner type
- awesome-llm-human-preference-datasets
- User
- awesome-RLHF
- Organization
Full report
- awesome-llm-human-preference-datasets
- Trust report
- awesome-RLHF
- Trust report
Choose awesome-llm-human-preference-datasets if…
- License: awesome-llm-human-preference-datasets is MIT, awesome-RLHF is Apache-2.0.
- Tags unique to awesome-llm-human-preference-datasets: awesome-list, datasets, eval, human-preferences.
- 当你需要对大型语言模型（LLM）进行微调，并希望使用经过人类评估的数据集来增强模型性能，尤其是在强化学习场景中时。
When NOT to use awesome-llm-human-preference-datasets
- NLP，LLM、，。
Choose awesome-RLHF if…
- License: awesome-RLHF is Apache-2.0, awesome-llm-human-preference-datasets is MIT.
- Tags unique to awesome-RLHF: deep-learning, depth-reinforcement-learning, human-feedback, large language models.
- When you are specifically interested in the resources that pertain to enhancing reinforcement learning algorithms with human feedback for developing advanced AI systems.
When NOT to use awesome-RLHF
- If your focus is exclusively on generic deep-learning or reinforcement-learning resources without the aspect of integrating human feedback into the training process.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (glgh/awesome-llm-human-preference-datasets) · observed Aug 6, 2026
- GitHub forks (glgh/awesome-llm-human-preference-datasets) · observed Aug 6, 2026
- Last push (glgh/awesome-llm-human-preference-datasets) · observed Oct 4, 2023
- License file (MIT) · observed Aug 6, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (opendilab/awesome-RLHF) · observed Aug 17, 2026
- GitHub forks (opendilab/awesome-RLHF) · observed Aug 17, 2026
- Last push (opendilab/awesome-RLHF) · observed May 20, 2026
- License file (Apache-2.0) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-llm-human-preference-datasets 390 · awesome-RLHF 4.4k (synced Aug 6, 2026).
Common questions
- What is the difference between awesome-llm-human-preference-datasets and awesome-RLHF?
- awesome-llm-human-preference-datasets: Curated list of Human Preference Datasets for LLM fine-tuning, RLHF, and eval. awesome-RLHF: A curated list of reinforcement learning with human feedback resources (continually updated). See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-llm-human-preference-datasets over awesome-RLHF?
- Choose awesome-llm-human-preference-datasets over awesome-RLHF when License: awesome-llm-human-preference-datasets is MIT, awesome-RLHF is Apache-2.0; Tags unique to awesome-llm-human-preference-datasets: awesome-list, datasets, eval, human-preferences; 当你需要对大型语言模型（LLM）进行微调，并希望使用经过人类评估的数据集来增强模型性能，尤其是在强化学习场景中时。.
- When should I choose awesome-RLHF over awesome-llm-human-preference-datasets?
- Choose awesome-RLHF over awesome-llm-human-preference-datasets when License: awesome-RLHF is Apache-2.0, awesome-llm-human-preference-datasets is MIT; Tags unique to awesome-RLHF: deep-learning, depth-reinforcement-learning, human-feedback, large language models; When you are specifically interested in the resources that pertain to enhancing reinforcement learning algorithms with human feedback for developing advanced AI systems.
- When should I avoid awesome-llm-human-preference-datasets?
- NLP，LLM、，。
- When should I avoid awesome-RLHF?
- If your focus is exclusively on generic deep-learning or reinforcement-learning resources without the aspect of integrating human feedback into the training process.
- Is awesome-llm-human-preference-datasets or awesome-RLHF more popular on GitHub?
- awesome-RLHF has more GitHub stars (4,422 vs 390). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-llm-human-preference-datasets and awesome-RLHF open source?
- Yes - both are open-source projects on GitHub (awesome-llm-human-preference-datasets: MIT, awesome-RLHF: Apache-2.0).
- Where can I find alternatives to awesome-llm-human-preference-datasets or awesome-RLHF?
- GraphCanon lists graph-backed alternatives at awesome-llm-human-preference-datasets alternatives and awesome-RLHF alternatives (awesome-llm-human-preference-datasets markdown twin, awesome-RLHF 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, awesome-llm-human-preference-datasets or awesome-RLHF?
- awesome-llm-human-preference-datasets: Dormant. awesome-RLHF: Steady. 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-llm-human-preference-datasets and awesome-RLHF?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-llm-human-preference-datasets trust report; awesome-RLHF trust report.