---
license: apache-2.0
pipeline_tag: image-text-to-text
---

### TinyLLaVA

We trained a TinyLLaVA model with 3.1B parameters, employing the same training settings as [TinyLLaVA](https://github.com/DLCV-BUAA/TinyLLaVABench). For the Language and Vision models, we chose [Phi-2](microsoft/phi-2) and [siglip-so400m-patch14-384](https://huggingface.co/google/siglip-so400m-patch14-384), respectively. The Connector was configured with a 2-layer MLP. The dataset used for training is the [ShareGPT4V](https://github.com/InternLM/InternLM-XComposer/blob/main/projects/ShareGPT4V/docs/Data.md) dataset.

### Usage

1. you need to download the generate file "generate_model.py".
2. running the following command:
```bash
python generate_model --model tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B --prompt 'you want to ask' --image '/path/to/related/image'
```
or  execute the following test code:
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
from generate_model import *

hf_path = 'tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B'
model = AutoModelForCausalLM.from_pretrained(hf_path, trust_remote_code=True)
config = model.config
tokenizer = AutoTokenizer.from_pretrained(hf_path, use_fast=False, model_max_length = config.tokenizer_model_max_length,padding_side = config.tokenizer_padding_side)
prompt="you want to ask"
image="/path/to/related/image"
output_text, genertaion_time = generate(prompt=prompt, image=image, model=model, tokenizer=tokenizer)
print_txt = (
        f'\r\n{"=" * os.get_terminal_size().columns}\r\n'
        '\033[1m Prompt + Generated Output\033[0m\r\n'
        f'{"-" * os.get_terminal_size().columns}\r\n'
        f'{output_text}\r\n'
        f'{"-" * os.get_terminal_size().columns}\r\n'
        '\r\nGeneration took'
        f'\033[1m\033[92m {round(genertaion_time, 2)} \033[0m'
        'seconds.\r\n'
    )
print(print_txt)
```
### Result

|                          model_name                          | vqav2 | gqa   | sqa | textvqa  | MM-VET | POPE | MME  | MMMU |
| :----------------------------------------------------------: | ----- | ------- | ----- | ----- | ------- | ----- | ------ | ------ |
| [bczhou/TinyLLaVA-3.1B](https://huggingface.co/bczhou/TinyLLaVA-3.1B) | 79.9  | 62.0    | 69.1  | 59.1 | 32.0  | 86.4  | 1464.9   | - |
| [tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B](https://huggingface.co/tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B) | 80.1 | 62.1   | 73.0 | 60.3 | 37.5 | 87.2  | 1466.4 | 38.4 |