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license: other
license_name: circlestone-labs-non-commercial-license
license_link: https://huggingface.co/circlestone-labs/Anima/blob/main/LICENSE.md
base_model:
- circlestone-labs/Anima
pipeline_tag: text-to-image
base_model_relation: quantized
---
# Anima-Base-FP8
This repository provides the **FP8 quantized version** of the [Anima-Base](https://huggingface.co/circlestone-labs/Anima) model.
It is optimized to significantly reduce VRAM usage while maintaining high-quality generation, making it much easier to run on consumer-grade GPUs with limited VRAM.
## Quantization Tool
This model was quantized using the following open-source tool:
* **Quantizer**: [comfy-dit-quantizer](https://github.com/bedovyy/comfy-dit-quantizer)
## Quantized Models
There are two models - FP8 and FP8-balanced
- FP8 (2.4GB) : (***recommend***) maximize generation speed while preserving quality as much as possible.
- FP8-balanced (2.7GB) : (***Personal Preference***) retain the prefix and suffix blocks intact, while exclusively modifying the Self-Attention and MLP layers. As a result, its performance is remarkably close to the original BF16 model.
| quant | sample |
|------------|----------------------|
| **bf16** ||
| **fp8** ||
| **fp8-balanced** ||
## Quantized layers
### fp8
```json
{
"format": "comfy_quant",
"block_names": ["net.blocks."],
"rules": [
{ "policy": "keep", "match": ["blocks.0", "blocks.1."] },
{ "policy": "float8_e4m3fn", "match": ["q_proj", "k_proj", "v_proj", "o_proj", "output_proj", ".mlp"] },
{ "policy": "nvfp4", "match": [] }
]
}
```
### fp8-balanced
```json
{
"format": "comfy_quant",
"block_names": ["net.blocks."],
"rules": [
{ "policy": "keep", "match": ["blocks.0.", "blocks.1.", "blocks.26.", "blocks.27."] },
{ "policy": "float8_e4m3fn", "match": ["self_attn.", ".mlp"] },
{ "policy": "nvfp4", "match": [] }
]
}
```
## Acknowledgments
* **Inspired by**: [Bedovyy](https://huggingface.co/Bedovyy) (This is his repo: [Anima-FP8](https://huggingface.co/Bedovyy/Anima-FP8)) |