RRepoGEO

REPOGEO REPORT · LITE

huggingface/pytorch_block_sparse

Default branch master · commit e71b5427 · scanned 6/9/2026, 9:23:04 AM

GitHub: 551 stars · 35 forks

AI VISIBILITY SCORE
28 /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
2 / 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/pytorch_block_sparse, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify maintenance status and unique value proposition in README

    Why:

    CURRENT
    The current README doesn't address maintenance status or comparison to modern alternatives like FlashAttention.
    COPY-PASTE FIX
    Add a prominent section (e.g., 'Project Status and Differentiators') to the README. Explicitly state the project's current maintenance status (e.g., 'This project is actively maintained for X purpose' or 'While some newer techniques like FlashAttention address specific attention sparsity, `pytorch_block_sparse` remains a unique solution for general block-sparse linear layers in PyTorch, offering custom CUDA kernels for performance.') and highlight its specific niche (e.g., 'focus on general block-sparse linear layers, distinct from attention-specific optimizations').
  • mediumreadme#2
    Clarify the existing license(s) in the README

    Why:

    CURRENT
    The README does not explicitly state the license(s) that apply to the project.
    COPY-PASTE FIX
    Add a 'License' section to the README, explicitly stating the license(s) under which the project is distributed (e.g., 'This project is licensed under [License Name 1] and [License Name 2]. See the LICENSE file for full details.').

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/pytorch_block_sparse
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepSpeed
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepSpeed · recommended 2×
  2. torch.nn.utils.prune · recommended 2×
  3. torch.cuda.amp · recommended 1×
  4. torch.utils.checkpoint.checkpoint · recommended 1×
  5. torch.quantization · recommended 1×
  • CATEGORY QUERY
    How can I reduce memory footprint and computation in PyTorch neural networks?
    you: not recommended
    AI recommended (in order):
    1. torch.cuda.amp
    2. torch.utils.checkpoint.checkpoint
    3. torch.quantization
    4. NVIDIA TensorRT
    5. torch.optim.SGD
    6. torch.optim.AdamW
    7. DeepSpeed
    8. torch.nn.utils.prune
    9. NVIDIA Apex
    10. torch.cuda.memory_summary()
    11. torch.cuda.max_memory_allocated()
    12. nvprof
    13. NVIDIA Nsight Systems

    AI recommended 13 alternatives but never named huggingface/pytorch_block_sparse. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are efficient ways to implement sparse linear layers in PyTorch models?
    you: not recommended
    AI recommended (in order):
    1. torch.nn.Embedding
    2. PyTorch's Native Sparse Tensors
    3. torch_sparse
    4. DeepSpeed
    5. NVIDIA's Apex
    6. torch.nn.utils.prune

    AI recommended 6 alternatives but never named huggingface/pytorch_block_sparse. 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 huggingface/pytorch_block_sparse?
    pass
    AI did not name huggingface/pytorch_block_sparse — 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/pytorch_block_sparse in production, what risks or prerequisites should they evaluate first?
    pass
    AI named huggingface/pytorch_block_sparse 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/pytorch_block_sparse solve, and who is the primary audience?
    pass
    AI named huggingface/pytorch_block_sparse explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of huggingface/pytorch_block_sparse. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/huggingface/pytorch_block_sparse.svg)](https://repogeo.com/en/r/huggingface/pytorch_block_sparse)
HTML
<a href="https://repogeo.com/en/r/huggingface/pytorch_block_sparse"><img src="https://repogeo.com/badge/huggingface/pytorch_block_sparse.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

huggingface/pytorch_block_sparse — 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