---
title: Bernini-Diffusers-qint8
canonical_url: "https://www.modelscope.cn/models/Gluttony10/Bernini-Diffusers-qint8"
md_url: "https://www.modelscope.cn/models/Gluttony10/Bernini-Diffusers-qint8.md"
repository: Gluttony10/Bernini-Diffusers-qint8
last_updated: 2026-06-15
license: apache-2.0
pipeline_tag: image-to-video
tasks:
  - image-to-video
model_type:
  - bernini
architectures:
  - BerniniModel
parameters: 49.9B
tensor_type:
  - BF16
  - I8
  - F32
library_name:
  - safetensors
  - diffusers
  - pytorch
frameworks:
  - pytorch
downloads: 166
stars: 1
---

# Bernini-Diffusers-qint8

> Bernini-Diffusers-qint8 - Gluttony10 在 ModelScope 开源的模型。Bernini-Diffusers-qint8

Gluttony10/Bernini-Diffusers-qint8 是 ModelScope 魔搭社区上的 49.9B 参数image-to-video模型，采用 apache-2.0 许可。

- **Repository**: Gluttony10/Bernini-Diffusers-qint8
- **License**: apache-2.0
- **Tasks**: image-to-video
- **Parameters**: 49.9B
- **Downloads**: 166
- **Stars**: 1
- **Last updated**: 2026-06-15

Source: https://www.modelscope.cn/models/Gluttony10/Bernini-Diffusers-qint8

---

# Bernini-Diffusers-qint8

This repository contains a qint8 quantized copy of `bytedance-community/Bernini-Diffusers` for Bernini full inference.

The quantized checkpoint was produced with `optimum.quanto` qint8 quantization. It is intended for the full Bernini pipeline only, including the MLLM semantic planner and Bernini rendering components. It does not contain Bernini-R weights and is not intended for Bernini-R inference.

## Source

- Source model: `bytedance-community/Bernini-Diffusers`
- Quantization: `optimum.quanto`, qint8 precision
- Target usage: Bernini full inference
- Non-target usage: Bernini-R inference
- License: Apache License 2.0, following the source model metadata

## Contents

The directory keeps the diffusers-style Bernini layout and adds the quanto quantization files for the Bernini checkpoint.

```text
Bernini-Diffusers-qint8/
  bernini/
    model.safetensors
    quantization_map.json
    qint8_info.json
  mllm/
  scheduler/
  t5_text_encoder/
  t5_tokenizer/
  vae/
  config.json
  configuration.json
  transformer_config.json
  transformer_2_config.json
```

Important files:

- `bernini/model.safetensors`: qint8 quantized Bernini checkpoint.
- `bernini/quantization_map.json`: `optimum.quanto` quantization map required to restore qint8 weights.
- `bernini/qint8_info.json`: local conversion metadata.
- `mllm/`, `t5_text_encoder/`, `t5_tokenizer/`, `vae/`, `scheduler/`, and configuration files: supporting assets copied from the source full Bernini diffusers package.

## Loading Notes

Load this directory as a local diffusers model directory in code that explicitly supports `optimum.quanto` qint8 restoration. The loader must read `bernini/model.safetensors` together with `bernini/quantization_map.json` before running Bernini full inference.

This package is not a replacement for Bernini-R and should not be used with Bernini-R-only inference code.