---
license: mit
tags:
  - diffusion
  - flow-matching
  - mlp
  - gaussian-mixture
---

# Flow Matching MLP Model

Flow Matching model with MLP vector field

## Model Details

- **Model Type**: flow_matching_mlp
- **Training Epochs**: 20000
- **Batch Size**: 2000
- **Learning Rate**: 0.001

## Architecture

- **Hidden Layers**: [100, 100, 100, 100]
- **Data Dimensionality**: 2
- **Standard Deviation**: 1.0
- **Scale**: 10.0

## 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/flow-matching-mlp", "pytorch_model.bin")
config_path = hf_hub_download("derekwong/flow-matching-mlp", "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 MLPVectorField class)
model = MLPVectorField(dim=config.dim, hiddens=config.hiddens)
model.load_state_dict(torch.load(model_path))
model.eval()
```

## Training

This model was trained using Flow Matching on 2D Gaussian mixture data.