---
title: avero-image
canonical_url: "https://www.modelscope.ai/models/NeuraAI/avero-image"
md_url: "https://www.modelscope.ai/models/NeuraAI/avero-image.md"
repository: NeuraAI/avero-image
last_updated: 2026-07-08
license: openrail
library_name:
  - pytorch
  - lora
downloads: 0
stars: 0
tags:
  - stable-diffusion
  - stable-diffusion-v1-5
  - text-to-image
  - fine-tuned
  - fashion
  - nature
  - city
  - portrait
  - food
  - animals
---

# avero-image

> avero-image - An open-source model by NeuraAI on ModelScope. Avero Image - Fine-tuned Stable Diffusion v1.5

NeuraAI/avero-image is a machine learning model on ModelScope. licensed under openrail.

- **Repository**: NeuraAI/avero-image
- **License**: openrail
- **Tags**: stable-diffusion, stable-diffusion-v1-5, text-to-image, fine-tuned, fashion, nature, city, portrait, food, animals
- **Downloads**: 0
- **Stars**: 0
- **Last updated**: 2026-07-08

Source: https://www.modelscope.ai/models/NeuraAI/avero-image

---

# Avero Image - Fine-tuned Stable Diffusion v1.5

This model is a fine-tuned version of [Stable Diffusion v1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5) trained on a diverse dataset spanning fashion, nature, city, portrait, food, and animal categories.

## Training Details

- **Base Model**: runwayml/stable-diffusion-v1-5
- **Training Steps**: 8,000
- **Resolution**: 512x512
- **Optimizer**: 8-bit Adam
- **Learning Rate**: 5e-6 with cosine schedule (500 warmup steps)
- **Batch Size**: 1 with gradient accumulation 4
- **Hardware**: NVIDIA T4
- **Precision**: Mixed FP16

## Categories

- **Fashion** (16 queries): Runway, editorial, street style, couture
- **Nature** (16 queries): Mountains, ocean, forest, landscapes
- **City** (15 queries): Urban, architecture, skyline, streets
- **Portrait** (12 queries): Bokeh, studio, artistic, environmental
- **Food** (10 queries): Gourmet, cuisine, desserts, plating
- **Animals** (10 queries): Wildlife, pets, nature scenes

## Usage

```python
from diffusers import StableDiffusionPipeline
import torch

pipe = StableDiffusionPipeline.from_pretrained(
    "itriedcoding/avero-image",
    torch_dtype=torch.float16,
).to("cuda")

image = pipe("a beautiful landscape", num_inference_steps=50).images[0]
image.save("output.png")
```

## Example Prompts

- "fashion runway gown"
- "mountain sunset landscape"
- "cyberpunk city night"
- "portrait bokeh lens"
- "gourmet plated dish"
- "wildlife lion savanna"