REPOGEO REPORT · LITE

imcaspar/gpt2-ml

Default branch master · commit f6286b16 · scanned 5/22/2026, 8:26:40 PM

GitHub: 1,706 stars · 328 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

35 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 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 imcaspar/gpt2-ml, 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 project's scope and open-source nature in the README's opening

Why:

CURRENT

# **GPT2** for Multiple Languages

[**中文说明**](./README_CN.md) | [**English**](./README.md)

COPY-PASTE FIX

# **GPT2** for Multiple Languages

This repository provides an open-source TensorFlow implementation of GPT-2, along with pretrained models specifically optimized for Chinese and other multilingual text generation tasks.

[**中文说明**](./README_CN.md) | [**English**](./README.md)

hightopics#2

Add more specific topics to clarify the project's nature and scope

Why:

CURRENT

bert, chinese, colab, gpt-2, nlp, pretrained-models, tensorflow, text-generation, tpu

COPY-PASTE FIX

bert, chinese, colab, gpt-2, nlp, pretrained-models, tensorflow, text-generation, tpu, open-source, llm, chinese-llm, gpt2-implementation

mediumhomepage#3
Add a homepage URL to the repository's 'About' section
Why:
COPY-PASTE FIX
```
https://github.com/imcaspar/gpt2-ml
```

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 imcaspar/gpt2-ml

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

ERNIE 3.0 Titan

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

ERNIE 3.0 Titan · recommended 1×
GLM-130B · recommended 1×
Pangu-α · recommended 1×
CPM-2 · recommended 1×
Wudao 2.0 · recommended 1×

CATEGORY QUERY
Looking for a pretrained large language model specifically for generating Chinese text.
you: not recommended
AI recommended (in order):
1. ERNIE 3.0 Titan
2. GLM-130B
3. Pangu-α
4. CPM-2
5. Wudao 2.0
6. BERT-wwm-ext
7. T5-Chinese
AI recommended 7 alternatives but never named imcaspar/gpt2-ml. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a robust language model capable of generating text in various non-English languages.
you: not recommended
AI recommended (in order):
1. Google Gemini
2. OpenAI GPT-4
3. Meta Llama 3
4. Cohere Command
5. Mistral Large / Mixtral 8x7B
6. T5
7. XLM-R
AI recommended 7 alternatives but never named imcaspar/gpt2-ml. This is the gap to close.
Show full AI answer

Objective checks

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

Metadata completeness
warn
Suggestion:
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 imcaspar/gpt2-ml?
pass
AI named imcaspar/gpt2-ml explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts imcaspar/gpt2-ml in production, what risks or prerequisites should they evaluate first?
pass
AI named imcaspar/gpt2-ml 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 imcaspar/gpt2-ml solve, and who is the primary audience?
pass
AI named imcaspar/gpt2-ml explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/imcaspar/gpt2-ml.svg)](https://repogeo.com/en/r/imcaspar/gpt2-ml)

HTML

<a href="https://repogeo.com/en/r/imcaspar/gpt2-ml"><img src="https://repogeo.com/badge/imcaspar/gpt2-ml.svg" alt="RepoGEO" /></a>

Pro

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imcaspar/gpt2-ml — 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