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<div align="center">
<p style="font-size:1.6em;font-weight:900;letter-spacing:0.04em;margin:0.2em 0 0.1em;">
β¨ DreamMachine Research β¨
</p>
<p style="font-size:1.05em;font-weight:500;color:#aaa;margin:0 0 1em;">
Billion-Item Neural Recommendation Β· Industrial AI Β· Open Research
</p>
[](https://huggingface.co/dream-machine-ai/Dream-Machine-08-09)
[](https://huggingface.co/datasets/dream-machine-ai/Dream-Machine-08-09-Dataset)
[](https://huggingface.co/spaces/dream-machine-ai/)
[](https://doi.org/10.5281/zenodo.21906715)
[](https://github.com/When-Summer-Understands-Winter/Dream-Machine/)
[](https://creativecommons.org/licenses/by-nc/4.0/)
<br/>
> *"We build the magic shop β the AI that knows exactly what you want before you do."*
**[π€ Models](#-models)** Β·
**[π¦ Datasets](#-datasets)** Β·
**[π Spaces](#-spaces)** Β·
**[π Research](#-research)** Β·
**[βοΈ License](#οΈ-license)**
</div>
---
## β¦ Our Mission
```
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β β¦ 10ΒΉβ°-item scale β recommend from billion-item catalogues β
β β¦ Open research β weights, data, code, paper all public β
β β¦ Reproducible β every result in the paper can be verified β
β β¦ Production-grade β from laptop to 250 Γ A100 cluster unchanged β
β β¦ Community-first β CC BY-NC 4.0, free for academic use β
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
```
> **Note on repository location:** All models, datasets, and Spaces are published under the
> **[dream-machine-ai](https://huggingface.co/dream-machine-ai)** account namespace.
> This organization page (`DreamMachine-AI`) serves as the team portal and research hub.
> Follow **[dream-machine-ai](https://huggingface.co/dream-machine-ai)** to get notified of new releases.
---
## π€ Models
### [Dream-Machine-08-09](https://huggingface.co/dream-machine-ai/Dream-Machine-08-09)
> **Billion-Item Neural Recommendation Sorcerer** β Multi-Hash Transformer Dual-Tower with RAG-Enhanced Recall
| Property | Value |
|:---------|:------|
| Architecture | Dual-Tower Transformer (Item + User) |
| Scale | Up to 10ΒΉβ° items, 10ΒΉβ° users |
| Embedding | Multi-Hash K=3, B=50K buckets |
| Layers | L=2 Transformer, H=8 heads, d=128 |
| Retrieval | FAISS HNSW, β€ 100 ms P99 |
| **AUC** | **0.4849** Β· HR@10 **1.0** Β· NDCG@10 **0.537** |
| Format | `safetensors` Β· `transformers`-compatible |
```python
from transformers import AutoModel
model = AutoModel.from_pretrained(
"dream-machine-ai/Dream-Machine-08-09", trust_remote_code=True
).eval()
```
**[β View Model Card](https://huggingface.co/dream-machine-ai/Dream-Machine-08-09)**
---
## π¦ Datasets
### [Dream-Machine-08-09-Dataset](https://huggingface.co/datasets/dream-machine-ai/Dream-Machine-08-09-Dataset)
> **E-Commerce Synthetic Dataset** β JD / Taobao schema, fully reproducible, zero real PII
| Split | Records | Format | Description |
|:------|--------:|:------:|:------------|
| `products` | 1,000 | JSONL | SKU catalogue β price, brand, category, attributes |
| `users` | 1,000 | JSONL | User profiles β demographics, interests, spending |
| `behaviors` | 5,000 | JSONL | Click / purchase / rating events |
```python
from datasets import load_dataset
products = load_dataset(
"dream-machine-ai/Dream-Machine-08-09-Dataset",
name="products", split="train"
)
```
**[β View Dataset Card](https://huggingface.co/datasets/dream-machine-ai/Dream-Machine-08-09-Dataset)**
---
## π Spaces
### [dream-machine-ai / README](https://huggingface.co/spaces/dream-machine-ai/README)
Interactive landing page β no installation required.
Explore the model architecture, scaling law charts, and end-to-end deployment guide.
**[β Open Space](https://huggingface.co/spaces/dream-machine-ai/)**
---
## π Research
### DreamMachine: A Billion-Item Neural Recommendation Sorcerer
> Wen, Fangjun Β· DreamMachine Research Team Β· August 2026
> DOI: [10.5281/zenodo.21906715](https://doi.org/10.5281/zenodo.21906715)
**Seven original contributions:**
| # | Contribution | Key Formula |
|:-:|:-------------|:------------|
| C1 | Multi-Hash Transformer Dual-Tower | Ξ΅_eff = (1 β e^{βN/2B})^K |
| C2 | Hierarchical Feature Architecture | ID β sparse β dense numeric |
| C3 | RAG-Enhanced Multi-Channel Recall | FAISS IVF-PQ + CF + rules |
| C4 | Cross-Attention Listwise Re-ranker | CTR / CVR / dwell-time |
| C5 | Uncertainty-Weighted InfoNCE | Learnable Ο_kΒ² per task |
| C6 | Closed-Form Scaling Laws | 9 breakpoints 10Β² β 10ΒΉβ° |
| C7 | Production Serving Stack | FastAPI + ONNX + INT8 |
```bibtex
@techreport{wen2026dreammachine,
title = {Magic Shop at Scale: Dream-Machine --- A Billion-Item
Real-Time Neural Recommendation Sorcerer},
author = {Wen, Fangjun},
year = {2026},
institution = {DreamMachine Research Team},
doi = {10.5281/zenodo.21906715},
url = {https://doi.org/10.5281/zenodo.21906715},
note = {Technical Report, August 2026. arXiv cs.IR / cs.LG}
}
```
---
## π Quick Start
```bash
pip install transformers torch faiss-cpu huggingface_hub datasets
```
```python
# 1. Load model
from transformers import AutoModel, AutoFeatureExtractor
model = AutoModel.from_pretrained(
"dream-machine-ai/Dream-Machine-08-09", trust_remote_code=True
).eval()
# 2. Load dataset
from datasets import load_dataset
ds = load_dataset("dream-machine-ai/Dream-Machine-08-09-Dataset",
name="products", split="train")
# 3. Start inference server
# git clone https://huggingface.co/dream-machine-ai/Dream-Machine-08-09
# python serve_hf.py --model_dir ./hf_model --port 8000
```
---
## π All Resources
| Resource | Link |
|:---------|:-----|
| π€ **Model** | [dream-machine-ai/Dream-Machine-08-09](https://huggingface.co/dream-machine-ai/Dream-Machine-08-09) |
| π¦ **Dataset** | [dream-machine-ai/Dream-Machine-08-09-Dataset](https://huggingface.co/datasets/dream-machine-ai/Dream-Machine-08-09-Dataset) |
| π **Space** | [spaces/dream-machine-ai](https://huggingface.co/spaces/dream-machine-ai/) |
| π’ **Org** | [huggingface.co/DreamMachine-AI](https://huggingface.co/DreamMachine-AI) |
| π **Paper** | [Zenodo 10.5281/zenodo.21906715](https://doi.org/10.5281/zenodo.21906715) |
| π» **GitHub** | [When-Summer-Understands-Winter/Dream-Machine](https://github.com/When-Summer-Understands-Winter/Dream-Machine/) |
---
## βοΈ License
All models, datasets, and code published by DreamMachine Research are licensed under the
**Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)**.
| β
Permitted | β Prohibited |
|:---|:---|
| Academic research & publication | Commercial products or services |
| Personal learning & experimentation | Revenue-generating deployments |
| Non-commercial derivative works | Sublicensing for profit |
| Citing in papers with attribution | Any business use without written permission |
> **Commercial use of any kind β including integrating model weights, code, or outputs into a product or service β requires explicit prior written consent from the author (Fangjun Wen).**
> Contact: fangjunwen168@outlook.com
[](https://creativecommons.org/licenses/by-nc/4.0/)
---
<div align="center">
<p style="font-size:1.05em;font-weight:700;margin:0.5em 0 0.3em;">
π€ <a href="https://huggingface.co/dream-machine-ai/Dream-Machine-08-09">Model</a> Β·
π¦ <a href="https://huggingface.co/datasets/dream-machine-ai/Dream-Machine-08-09-Dataset">Dataset</a> Β·
π <a href="https://huggingface.co/spaces/dream-machine-ai/">Space</a> Β·
π <a href="https://doi.org/10.5281/zenodo.21906715">Paper</a> Β·
π» <a href="https://github.com/When-Summer-Understands-Winter/Dream-Machine/">GitHub</a>
</p>
**DreamMachine Research Team** Β· Fangjun Wen Β· August 2026
`// built with focus Β· DreamMachine Research`
</div>
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