REPOGEO REPORT · LITE
Instruction-Tuning-with-GPT-4/GPT-4-LLM
Default branch main · commit 80cda626 · scanned 7/1/2026, 8:08:10 PM
GitHub: 4,332 stars · 309 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Instruction-Tuning-with-GPT-4/GPT-4-LLM, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Clarify the README's opening sentence to emphasize 'dataset'
Why:
CURRENTThis is the repo for the GPT-4-LLM, which aims to share data generated by GPT-4 for building an instruction-following LLMs with supervised learning and reinforcement learning.
COPY-PASTE FIXThis repository, GPT-4-LLM, provides high-quality instruction-following datasets generated by GPT-4 for building and fine-tuning large language models (LLMs) through supervised learning and reinforcement learning.
- mediumtopics#2Add 'dataset' and 'data' to repository topics
Why:
CURRENTalpaca, chatgpt, gpt-4, instruction-tuning, llama
COPY-PASTE FIXalpaca, chatgpt, gpt-4, instruction-tuning, llama, dataset, data
- lowabout#3Expand the repository description to include the project name and core offering
Why:
CURRENTInstruction Tuning with GPT-4
COPY-PASTE FIXGPT-4-LLM: High-quality instruction-following datasets generated by GPT-4 for instruction tuning large language models.
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Alpaca (Stanford Alpaca) · recommended 1×
- ShareGPT (OpenAssistant Conversations Dataset - OACD) · recommended 1×
- Dolly 2.0 (Databricks Dolly-v2-12b) · recommended 1×
- FLAN (Fine-tuned LAnguage Net) · recommended 1×
- P3 (Public Pool of Prompts) · recommended 1×
- CATEGORY QUERYWhere can I find high-quality instruction-following datasets for fine-tuning large language models?you: not recommendedAI recommended (in order):
- Alpaca (Stanford Alpaca)
- ShareGPT (OpenAssistant Conversations Dataset - OACD)
- Dolly 2.0 (Databricks Dolly-v2-12b)
- FLAN (Fine-tuned LAnguage Net)
- P3 (Public Pool of Prompts)
- Super-NaturalInstructions
AI recommended 6 alternatives but never named Instruction-Tuning-with-GPT-4/GPT-4-LLM. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat resources offer instruction tuning data generated by advanced AI for building custom LLMs?you: not recommendedAI recommended (in order):
- Databricks Dolly 2.0 Dataset (databricks/dolly)
- Alpaca Dataset (tatsu-lab/stanford_alpaca)
- ShareGPT
- Vicuna (lmsys/vicuna)
- OpenAssistant Conversations Dataset (LAION-AI/Open-Assistant)
- GPT-4-Alpaca (Instruction-Tuning-with-GPT-4/GPT-4-Alpaca)
- WizardLM (nlpx-ucb/WizardLM)
- LIMA (epfLLM/lima)
- Self-Instruct (yizhongw/self-instruct)
AI recommended 9 alternatives but never named Instruction-Tuning-with-GPT-4/GPT-4-LLM. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of Instruction-Tuning-with-GPT-4/GPT-4-LLM?passAI did not name Instruction-Tuning-with-GPT-4/GPT-4-LLM — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts Instruction-Tuning-with-GPT-4/GPT-4-LLM in production, what risks or prerequisites should they evaluate first?passAI did not name Instruction-Tuning-with-GPT-4/GPT-4-LLM — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo Instruction-Tuning-with-GPT-4/GPT-4-LLM solve, and who is the primary audience?passAI did not name Instruction-Tuning-with-GPT-4/GPT-4-LLM — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
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Instruction-Tuning-with-GPT-4/GPT-4-LLM — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite