REPOGEO REPORT · LITE
deepseek-ai/Engram
Default branch main · commit fb7f84a2 · scanned 6/25/2026, 2:32:59 AM
GitHub: 4,466 stars · 341 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.
3 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 deepseek-ai/Engram, 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#1Reposition README's opening to clarify LLM sparsity/knowledge lookup focus
Why:
CURRENTThe current README starts with '## 1. Introduction' after an initial block of links.
COPY-PASTE FIXAdd the following text directly after the initial link block and before '## 1. Introduction': 'Engram provides the official implementation for **Conditional Memory via Scalable Lookup**, introducing a novel axis of sparsity for Large Language Models. This module modernizes classic N-gram embeddings to enable efficient, O(1) knowledge lookup, offering a powerful alternative and complement to traditional MoE architectures for enhancing LLM knowledge and reasoning capabilities.'
- hightopics#2Add specific topics for LLM sparsity and knowledge lookup
Why:
CURRENT(none)
COPY-PASTE FIXlarge-language-models, llm, sparsity, conditional-memory, knowledge-lookup, n-gram, deep-learning, machine-learning, ai
- mediumhomepage#3Add a homepage link to the project's About section
Why:
COPY-PASTE FIXhttps://huggingface.co/deepseek-ai
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.
- Faiss · recommended 1×
- Pinecone · recommended 1×
- Weaviate · recommended 1×
- Chroma · recommended 1×
- Milvus · recommended 1×
- CATEGORY QUERYHow to enhance large language model knowledge lookup efficiency beyond traditional methods?you: not recommendedAI recommended (in order):
- Faiss
- Pinecone
- Weaviate
- Chroma
- Milvus
- Qdrant
- Elasticsearch
AI recommended 7 alternatives but never named deepseek-ai/Engram. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat are alternative sparsity techniques for scaling large language models, besides Mixture-of-Experts?you: not recommendedAI recommended (in order):
- LAMP
- SNIP
- GraSP
- Rigged Lottery Ticket Hypothesis
- Sparse Evolutionary Training (SET)
- SparseGPT
- Lottery Ticket Hypothesis (LTH)
- Sparse-Quantized Neural Networks (SQNNs)
- LoRA
- Compacter
- DistilBERT
AI recommended 11 alternatives but never named deepseek-ai/Engram. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- 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 deepseek-ai/Engram?passAI named deepseek-ai/Engram explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts deepseek-ai/Engram in production, what risks or prerequisites should they evaluate first?passAI named deepseek-ai/Engram 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 deepseek-ai/Engram solve, and who is the primary audience?passAI named deepseek-ai/Engram 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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deepseek-ai/Engram — 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