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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Foundation model for tiny devices; 14mb, 26m params, 1-6k toks/sec on mobiles, wearables smart home and robots.
| Date | Stars |
|---|---|
| 2026-07-31 | 3320 |
| 2026-08-03 | 3320 |
| 2026-08-05 | 3369 |
| 2026-08-06 | 3369 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Needle
<img src="assets/banner.png" alt="Logo" style="border-radius: 30px; width: 100%;">
A 26m parameter "[Simple Attention Network](https://arxiv.org/abs/2607.18363)" for function calling that you can even finetune locally on your Mac/PC.
In production, Needle runs on [Cactus](https://github.com/cactus-compute/cactus) at 6000 toks/sec prefill and 1200 decode speed.
Weights are fully open on [Cactus-Compute/needle](https://huggingface.co/Cactus-Compute/needle), as well as the dataset generation.
```
d=512, 8H/4KV, BPE=8192
┌──────────────┐
│ Tool Call │
└──────┬───────┘
┌┴──────────┐
│ Softmax │
└─────┬─────┘
┌─────┴─────┐
│ Linear (T)│ ← tied
└─────┬─────┘
┌─────┴─────┐
│ ZCRMSNorm │
└─────┬─────┘
┌────────┴────────┐
│ Decoder x 8 │
│┌───────────────┐│
││ ZCRMSNorm ││
││ Masked Self ││
││ Attn + RoPE ││
││ Gated Residual││
│├───────────────┤│
┌──────────────┐ ││ ZCRMSNorm ││
│ Encoder x 12 │──────────────────────▶Cross Attn ││
│ │ ││ Gated Residual││
│ ┌──────────┐ │ │└───────────────┘│
│ │ZCRMSNorm │ │ └────────┬────────┘
│ │Self Attn │ │ ┌─────┴─────┐
│ │ GQA+RoPE │ │ │ Embedding │ ← shared
│ │Gated Res │ │ └─────┬─────┘
│ │ │ │ ┌───────┴───────-┐
│ │ (no FFN) │ │ │[EOS]<tool_call>│
│ └──────────┘ │ │ + answer │
│ │ └───────────────-┘
└──────┬───────┘
│
┌────┴──────┐
│ Embedding │
└────┬──────┘
│
┌────┴──────┐
│ Text │
│ query │
└───────────┘
```
- Pretrained on 16 TPU v6e for 200B tokens (27hrs).
- Post-trained on 2B tokens of single-shot function call dataset (45mins).
Needle is an experimental run for Simple Attention Networks, geared at redefining tiny AI for consumer devices (phones, watches, glasses...).
So while it beats FunctionGemma-270m, Qwen-0.6B, Graninte-350m, LFM2.5-350m on single-shot function call for personal AI,
Those model are have more scope/capacity and excel in conversational settings. Also, small models can be finicky.
Please use the UI in the next section to test on your own tools, and finetune accordingly, at the click of a button.
## Quickstart
```bash
git clone https://github.com/cactus-compute/needle.git
cd needle && source ./setup
needle playground
```
Opens a web UI at http://127.0.0.1:7860 where you can test and finetune on your own tools. Weights are auto-downloaded.
## Usage (Python)
```python
from needle import SimpleAttentionNetwork, load_checkpoint, generate, get_tokenizer
params, config = load_checkpoint("checkpoints/needle.pkl")
model = SimpleAttentionNetwork(config)
tokenizer = get_tokenizer()
result = generate(
model, params, tokenizer,
query="What's the weather in San Francisco?",
tools='[{"name":"get_weather","description":"Get current weather for a city.","parameters":{"location":{"type":"string","description":"City name.","required":true}}}]',
stream=False,
)
print(result)
# [{"name":"get_weather","arguments":{"location":"San Francisco"}}]
```
## FiExcerpt of 7,194 characters
Read on GitHub
Henry Ndubuaku · Cactus Compute · United Kingdom
210
Noah Cylich
9
Justin Lee
5
Karen Mosoyan
5
Jakub Mroz · Cactus (YC S25)
4
Anton Osika
1
1
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:1244dbf6e9aa6593, topic:llm