---
title: FG-CLIP
canonical_url: "https://www.modelscope.cn/models/AXERA-TECH/FG-CLIP"
md_url: "https://www.modelscope.cn/models/AXERA-TECH/FG-CLIP.md"
repository: AXERA-TECH/FG-CLIP
last_updated: 2026-01-21
license: apache-2.0
base_model:
  - qihoo360/fg-clip2-base
base_model_relation: finetune
library_name:
  - pytorch
frameworks:
  - pytorch
language:
  - en
downloads: 35
stars: 0
tags:
  - CLIP
  - FG-CLIP
  - FG-CLIP2
  - "Image-Text Encoder"
---

# FG-CLIP

> FG-CLIP - AXERA-TECH 在 ModelScope 开源的模型。The version of FG-CLIP2 has been converted to run on the Axera NPU using w8a16 quantization. Compatible with Pulsar2 version: 4.2

AXERA-TECH/FG-CLIP 是 ModelScope 魔搭社区上的机器学习模型，采用 apache-2.0 许可，基于 qihoo360/fg-clip2-base 构建。

- **Repository**: AXERA-TECH/FG-CLIP
- **License**: apache-2.0
- **Base model**: qihoo360/fg-clip2-base
- **Tags**: CLIP, FG-CLIP, FG-CLIP2, Image-Text Encoder
- **Downloads**: 35
- **Stars**: 0
- **Last updated**: 2026-01-21

Source: https://www.modelscope.cn/models/AXERA-TECH/FG-CLIP

---

# FG-CLIP2

The version of FG-CLIP2 has been converted to run on the Axera NPU using w8a16 quantization. Compatible with Pulsar2 version: 4.2

If you want to know how to convert the FG-CLIP2 model into an axmodel that can run on the axera npu board, please read [this link](https://github.com/Jordan-5i/FG-CLIP/tree/main/ax_tools) in detail.


## Support Platform
- AX650

## End-of-board inference time
  | Stage | Time |
  |------|------|
  | image_encoder |  125.197 ms  | 
  | text_encoder |  10.817 ms  | 

## How to use

Download all files from this repository to the device

Run the following command:
```bash
python3 run_axmodel.py 
```
Model input and output examples are as follows:
1. the image you want to input:

   ![](bedroom.jpg)

2. The description of the image content:

```bash
   [
    "一个简约风格的卧室角落，黑色金属衣架上挂着多件米色和白色的衣物，下方架子放着两双浅色鞋子，旁边是一盆绿植，左侧可见一张铺有白色床单和灰色枕头的床。",
    "一个简约风格的卧室角落，黑色金属衣架上挂着多件红色和蓝色的衣物，下方架子放着两双黑色高跟鞋，旁边是一盆绿植，左侧可见一张铺有白色床单和灰色枕头的床。",
    "一个简约风格的卧室角落，黑色金属衣架上挂着多件米色和白色的衣物，下方架子放着两双运动鞋，旁边是一盆仙人掌，左侧可见一张铺有白色床单和灰色枕头的床。",
    "一个繁忙的街头市场，摊位上摆满水果，背景是高楼大厦，人们在喧闹中购物。"
  ]
```

3. The similarity between the output of the image encoder and the text encoder is

   ```bash
   Logits per image: tensor([[9.8757e-01, 4.7755e-03, 7.6510e-03, 1.3484e-14]], dtype=torch.float64)
   ```