README.md

---
license: mit
tags:
  - diffusion
  - discrete-flow-matching
  - moons
  - discrete
---

# Discrete Flow Matching Model

Discrete Flow Matching model trained on discretized Moons dataset

## Model Details

- **Model Type**: discrete_flow_matching_moons
- **Training Epochs**: 20000
- **Batch Size**: 2000
- **Learning Rate**: 0.001
- **CFG Parameter (eta)**: 0.1
- **Vocabulary Size**: 128
- **Data Scale**: 10.0
- **Data Standard Deviation**: 1.0

## Architecture

- **Embedding Dimension**: 128
- **Data Dimensionality**: 2

## Usage

```python
from huggingface_hub import hf_hub_download
import torch
from model_config import FlowMatchingConfig

# Download model and config
model_path = hf_hub_download("derekwong/discrete-flow-matching-moons", "pytorch_model.bin")
config_path = hf_hub_download("derekwong/discrete-flow-matching-moons", "config.json")

# Load config
import json
with open(config_path) as f:
    config_dict = json.load(f)
config = FlowMatchingConfig.from_dict(config_dict)

# Load model (you'll need the DiscreteFlow class)
model = DiscreteFlow(dim=config.dim, h=config.embedding_dimension, v=config.vocab_size)
model.load_state_dict(torch.load(model_path))
model.eval()
```

## Training

This model was trained using Discrete Flow Matching on the discretized Moons dataset.