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license: mit
tags:
- sparseflow
- sparse-attention
- efficient-nlp
datasets:
- gsm8k
- lighteval/MATH
- allenai/ai2_arc
- tau/commonsense_qa
- piqa
- allenai/sciq
- trivia_qa
- nq_open
- wikitext
---
# SparseFlow v8
Efficient language model with **sparse attention** and **persistent memory**.
## 📊 REAL Measured Metrics
| Metric | Value |
|--------|-------|
| Parameters | 71,359,746 |
| Perplexity | 14.77 |
| Attention Sparsity | 87.5% |
| Channel Sparsity | 75.0% |
| Peak Memory | 3.67 GB |
## 🏗️ Architecture
- **Sparse Token Attention**: Attends to top-64 tokens per position
- **Sparse Channel FFN**: Activates top-128 channels
- **Persistent Memory**: 20,000 memory vectors
- **8 Transformer layers** with 512 dim
## 📚 Training Data
Open source datasets only:
- GSM8K, MATH (mathematics)
- ARC, OpenBookQA, SciQ (science & reasoning)
- CommonsenseQA, PIQA (common sense)
- TriviaQA, Natural Questions (factual)
- WikiText-103 (language modeling)
## 👨💻 Author
**Logo (Mike Amega)** — Ame Web Studio
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