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--- |
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license: apache-2.0 |
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pipeline_tag: image-text-to-text |
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--- |
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### TinyLLaVA |
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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. |
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### Usage |
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1. you need to download the generate file "generate_model.py". |
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2. running the following command: |
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```bash |
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python generate_model --model tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B --prompt 'you want to ask' --image '/path/to/related/image' |
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``` |
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or execute the following test code: |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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from generate_model import * |
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hf_path = 'tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B' |
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model = AutoModelForCausalLM.from_pretrained(hf_path, trust_remote_code=True) |
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config = model.config |
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tokenizer = AutoTokenizer.from_pretrained(hf_path, use_fast=False, model_max_length = config.tokenizer_model_max_length,padding_side = config.tokenizer_padding_side) |
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prompt="you want to ask" |
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image="/path/to/related/image" |
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output_text, genertaion_time = generate(prompt=prompt, image=image, model=model, tokenizer=tokenizer) |
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print_txt = ( |
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f'\r\n{"=" * os.get_terminal_size().columns}\r\n' |
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'\033[1m Prompt + Generated Output\033[0m\r\n' |
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f'{"-" * os.get_terminal_size().columns}\r\n' |
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f'{output_text}\r\n' |
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f'{"-" * os.get_terminal_size().columns}\r\n' |
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'\r\nGeneration took' |
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f'\033[1m\033[92m {round(genertaion_time, 2)} \033[0m' |
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'seconds.\r\n' |
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) |
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print(print_txt) |
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``` |
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### Result |
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| model_name | vqav2 | gqa | sqa | textvqa | MM-VET | POPE | MME | MMMU | |
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| :----------------------------------------------------------: | ----- | ------- | ----- | ----- | ------- | ----- | ------ | ------ | |
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| [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 | - | |
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| [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 | |