Create README.md

README.md

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+---
+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 *
+model = AutoModelForCausalLM.from_pretrained("tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B", trust_remote_code=True)
+config = model.config
+tokenizer = AutoTokenizer.from_pretrained("tinyllava/TinyLLaVA-Phi-2-SigLIP-3.1B", 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  | 1464.98   | - |
+| [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 |