REPOGEO REPORT · LITE

huggingface/alignment-handbook

Default branch main · commit 1de1fc99 · scanned 5/19/2026, 9:58:25 PM

GitHub: 5,602 stars · 489 forks

Scan history for this repo

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.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

27 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

1 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

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 huggingface/alignment-handbook, 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.

OVERALL DIRECTION

highreadme#1

Clarify the first descriptive sentence after the H1

Why:

CURRENT

Robust recipes to continue pretraining and to align language models with human and AI preferences.

COPY-PASTE FIX

The Alignment Handbook provides robust, practical recipes and runnable code to continue pretraining and align language models with human and AI preferences.

mediumtopics#2
Add more specific topics to improve categorization
Why:
CURRENT
```
llm, rlhf, transformers
```
COPY-PASTE FIX
```
llm, rlhf, transformers, fine-tuning, dpo, alignment, guide, tutorial
```

mediumreadme#3

Add a clear differentiator statement to the README

Why:

COPY-PASTE FIX

Add this sentence at the beginning of the 'What is this?' section: 'Unlike academic papers or generic libraries, this handbook provides a comprehensive, code-centric guide with runnable examples for implementing state-of-the-art LLM alignment techniques.'

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.

Recall

0 / 2

0% of queries surface huggingface/alignment-handbook

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

huggingface/trl

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

huggingface/trl · recommended 2×
DeepMind's TRPO/PPO implementations · recommended 1×
OpenAI's InstructGPT/ChatGPT pipeline · recommended 1×
Original DPO paper implementations · recommended 1×
Anthropic's research · recommended 1×

CATEGORY QUERY
How to align large language models with human preferences using reinforcement learning?
you: not recommended
AI recommended (in order):
1. Hugging Face's TRL (huggingface/trl)
2. DeepMind's TRPO/PPO implementations
3. OpenAI's InstructGPT/ChatGPT pipeline
4. Original DPO paper implementations
5. Anthropic's research
6. LightGBM (microsoft/LightGBM)
7. XGBoost (dmlc/xgboost)
8. PyTorch (pytorch/pytorch)
9. TensorFlow (tensorflow/tensorflow)
10. Vowpal Wabbit (VowpalWabbit/vowpal_wabbit)
11. RLlib (ray-project/ray)
AI recommended 11 alternatives but never named huggingface/alignment-handbook. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking practical guidelines for fine-tuning LLMs to follow instructions and be safe.
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers (huggingface/transformers)
2. PEFT (huggingface/peft)
3. TRL (huggingface/trl)
4. OpenAI API
5. Argilla (argilla-io/argilla)
6. Snorkel AI
7. Scale AI
8. Appen
9. Anthropic's Constitutional AI
10. Garak (leondf/garak)
11. Guardrails AI (guardrails-ai/guardrails)
12. Hugging Face Evaluate (huggingface/evaluate)
13. Arize AI
14. WhyLabs
15. LangChain (langchain-ai/langchain)
16. LlamaIndex (run-llama/llama_index)
AI recommended 16 alternatives but never named huggingface/alignment-handbook. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

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 huggingface/alignment-handbook?
pass
AI did not name huggingface/alignment-handbook — 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 huggingface/alignment-handbook in production, what risks or prerequisites should they evaluate first?
pass
AI named huggingface/alignment-handbook explicitly
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 huggingface/alignment-handbook solve, and who is the primary audience?
pass
AI did not name huggingface/alignment-handbook — 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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MARKDOWN (README)

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huggingface/alignment-handbook — 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