https://github.com/ora-io/opml
OPML: OPtimistic Machine Learning on Blockchain
https://github.com/ora-io/opml
ai blockchain ethereum machine opml optimistic smart-contracts web3
Last synced: 5 months ago
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OPML: OPtimistic Machine Learning on Blockchain
- Host: GitHub
- URL: https://github.com/ora-io/opml
- Owner: ora-io
- License: mit
- Created: 2023-07-07T03:35:39.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-12-11T06:24:50.000Z (10 months ago)
- Last Synced: 2025-05-05T02:48:22.980Z (5 months ago)
- Topics: ai, blockchain, ethereum, machine, opml, optimistic, smart-contracts, web3
- Language: Solidity
- Homepage:
- Size: 5.34 MB
- Stars: 307
- Watchers: 27
- Forks: 67
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# OPML: OPtimistic Machine Learning on Blockchain
OPML enables off-chain AI model inference using optimistic approach with an on chain interactive dispute engine implementing fault proofs.
For more in-depth information, refer to the [project wiki](https://github.com/hyperoracle/opml/wiki).
You can also find a tutorial on building a straightforward handwritten digit recognition DNN model (MNIST) within OPML in the [`docs/tutorial.md`](docs/tutorial.md).
## Building
Pre-requisites: Go (Go 1.19), Node.js, Make, and CMake.
```
git clone git@github.com:hyperoracle/opml.git --recursive
make build
```
## Examples
The script files [`demo/challenge_simple.sh`](demo/challenge_simple.sh) presents an example scenario (a DNN model for MNIST) demonstrating the whole process of a fault proof, including the challenge game and single step verification.
To test the example, we should first start a local node:
```shell
npx hardhat node
```
Then we can run:
```shell
bash ./demo/challenge_simple.sh
```
A large language model, the llama example is provided in the branch ["llama"](https://github.com/hyperoracle/opml/tree/llama) (It also works for llama 2).
## Roadmap
🔨 = Pending
🛠= Work In Progress
✅ = Feature complete
| Feature | Status |
| ------- | :------: |
| **Supported Model** | |
| DNN for MNIST | ✅ |
| LLaMA | ✅ |
| General DNN Model (Onnx Support) | 🛠|
| Traditional ML Algorithm (Decision Tree, KNN etc) | 🔨 |
| **Mode** | |
| Inference| ✅ |
| Training | 🔨 |
| Fine-tuning | 🔨 |
| **Optimization** | |
| ZK Fault Proof with zkOracle and zkWASM | 🛠|
| GPU Acceleration | 🛠|
| High Performance VM | 🛠|
| **Functionality** | |
| User-Friendly SDK| 🛠|
## Project Structure
```
mlgo -- A tensor library for machine learning in pure Golang that can run on MIPS.
mlvm -- A MIPS runtime with ML execution
contracts -- A Merkleized MIPS processor on chain + the challenge logic
```
## License
This code is MIT licensed.
Part of this code is borrowed from `ethereum-optimism/cannon`
Note: This code is unaudited. It in NO WAY should be used to secure any money until a lot more
testing and auditing are done.