Feature Extraction
Transformers
PyTorch
Chinese
English
recommendation
dual-tower
transformer
multi-hash-embedding
Instructions to use DreamMachine-AI/Dream-Machine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DreamMachine-AI/Dream-Machine with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DreamMachine-AI/Dream-Machine")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DreamMachine-AI/Dream-Machine", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 6,596 Bytes
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license: cc-by-nc-4.0
language:
- zh
- en
tags:
- recommendation
- dual-tower
- transformer
- multi-hash-embedding
- pytorch
library_name: transformers
pipeline_tag: feature-extraction
---
<div style="max-width:100%;overflow:hidden;">
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</div>
<div align="center">
<p style="font-size:1.5em;font-weight:900;letter-spacing:0.03em;margin:0.2em 0 0.1em;">
β¨ Dream-Machine β Billion-Item Neural Recommendation Sorcerer β¨
</p>
<p style="font-size:1.0em;font-weight:500;color:#aaa;margin:0 0 1em;">
Multi-Hash Transformer Dual-Tower Β· RAG-Enhanced Β· Production-Grade Β· 10<sup>10</sup> Scale
</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://creativecommons.org/licenses/by-nc/4.0/)
</div>
---
## π Repository Notice
> **This repository is the official DreamMachine-AI organization listing.**
> The full model weights, code, and documentation are published under the
> **[dream-machine-ai](https://huggingface.co/dream-machine-ai)** account namespace.
| Resource | Location |
|:---------|:---------|
| π€ **Full Model Card + Weights** | [dream-machine-ai/Dream-Machine-08-09](https://huggingface.co/dream-machine-ai/Dream-Machine-08-09) |
| π¦ **Training Dataset** | [dream-machine-ai/Dream-Machine-08-09-Dataset](https://huggingface.co/datasets/dream-machine-ai/Dream-Machine-08-09-Dataset) |
| π **Interactive Space** | [spaces/dream-machine-ai](https://huggingface.co/spaces/dream-machine-ai/) |
| π’ **Organization Hub** | [DreamMachine-AI](https://huggingface.co/DreamMachine-AI) |
| π **Technical Report** | [Zenodo 10.5281/zenodo.21906715](https://doi.org/10.5281/zenodo.21906715) |
| π» **Source Code** | [GitHub / Dream-Machine](https://github.com/When-Summer-Understands-Winter/Dream-Machine/) |
---
## β‘ Quick Load
```python
from transformers import AutoConfig, AutoModel
model = AutoModel.from_pretrained(
"dream-machine-ai/Dream-Machine-08-09",
trust_remote_code=True,
).eval()
```
```python
from huggingface_hub import snapshot_download
# Full model repository
model_path = snapshot_download(repo_id="dream-machine-ai/Dream-Machine-08-09")
# Training dataset
dataset_path = snapshot_download(
repo_id="dream-machine-ai/Dream-Machine-08-09-Dataset",
repo_type="dataset",
)
```
---
## π Benchmarks
| Metric | Value |
|:-------|:-----:|
| **AUC** | **0.4849** |
| **HR@10** | **1.0** |
| **NDCG@10** | **0.537** |
| E2E Latency | **β€ 100 ms** |
| Max Catalogue | **10ΒΉβ° items** |
---
## βοΈ License
This project is 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">
**Paper**: [DreamMachine: A Billion-Item Neural Recommendation Sorcerer](https://doi.org/10.5281/zenodo.21906715)
**Author**: Fangjun Wen Β· DreamMachine Research Team Β· August 2026
`// built with focus Β· DreamMachine Research`
</div>
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