Hugging Face's logo

FreedomIntelligence
/
LongLLaVA-53B-A13B

Image-Text-to-Text
Transformers
Safetensors
llava_jamba
text-generation
custom_code
Inference Endpoints
Model card Files Community
3
LongLLaVA-53B-A13B
File size: 1,528 Bytes 
0746f2a
 
 
 
 
 
75b11e0
0746f2a
 
 
 
 
 
2b49032
0746f2a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
75b11e0
0746f2a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
 
---
license: mit
---
![header](./assets/header.png) 

<p align="center">
   📃 <a href="" target="_blank">Paper</a> • 🌐 <a href="" target="_blank">Demo</a> • 📃 <a href="https://github.com/FreedomIntelligence/LongLLaVA" target="_blank">LongLLaVA</a> 
</p>

![efficiency](./assets/singleGPU.png) 

## 🌈 Update

* **[2024.09.05]** LongLLaVA repo is published！🎉 

## Architecture

<details>
  <summary>Click to view the architecture image</summary>

  ![Architecture Image](./assets/arch.png)

</details>


## Results

<details>
  <summary>Click to view the Results</summary>

  - Main Results
      ![Main Results](./assets/result1.png) 
  - Diagnostic Results
      ![Diagnostic Results](./assets/diaresult.png)
  - Video-NIAH
      ![Video-NIAH](./assets/NIAH.png)

</details>



## Results reproduction

### Data DownLoad and Construction

<details>
  <summary>Dataset Taxonomy</summary>

  ![Dataset](./assets/dataset.png) 

</details>

<details>
  <summary>Dataset DownLoading and Construction</summary>

   > Coming Soon~

</details>



### Evaluation

> Model checkpoint is Coming Soon~



## Citation

```
@misc{wang2024longllavascalingmultimodalllms,
      title={LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via Hybrid Architecture}, 
      author={Xidong Wang and Dingjie Song and Shunian Chen and Chen Zhang and Benyou Wang},
      year={2024},
      eprint={2409.02889},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2409.02889}, 
}
```