Create README.md

README.md

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+---
+license: apache-2.0
+pipeline_tag: image-text-to-text
+---
+### TinyLLaVA
+
+We have released two multimodal large models smaller than 1B, and the inference speed of both models on CPU is very fast.
+
+See the list below for the details of each model:
+
+- [TinyLLaVA-0.55B](https://huggingface.co/jiajunlong/TinyLLaVA-0.55B)
+- [TinyLLaVA-0.89B](https://huggingface.co/jiajunlong/TinyLLaVA-0.89B)
+
+### Usage
+
+1. you can download the generate file "generate_model.py"
+2. running the following command:
+
+```bash
+python generate_model --model [MODEL_NAME] --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("jiajunlong/TinyLLaVA-0.55B", trust_remote_code=True)
+config = model.config
+tokenizer = AutoTokenizer.from_pretrained("jiajunlong/TinyLLaVA-0.55B", use_fast=False, model_max_length = config.tokenizer_model_max_length,padding_side = config.tokenizer_padding_side)
+prompt="what is umusual about this image?"
+image="joke.png"
+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                          | gqa   | textvqa | sqa   | vqav2 | MME     | MMB   | MM-VET | GPU            | CPU        |
+| :----------------------------------------------------------: | ----- | ------- | ----- | ----- | ------- | ----- | ------ | -------------- | ---------- |
+| [TinyLLaVA-1.5B](https://huggingface.co/bczhou/TinyLLaVA-1.5B) | 60.3  | 51.7    | 60.3  | 76.9  | 1276.5  | 55.2  | 25.8   | 11.9 it/s      | 0.35 it/s  |
+| [TinyLLaVA-0.55B](https://huggingface.co/jiajunlong/TinyLLaVA-0.55B) | 53.87 | 44.02   | 54.09 | 71.74 | 1118.75 | 37.8  | 20     | 11.0 it/s      | 0.67 it/s  |
+| [TinyLLaVA-0.89B](https://huggingface.co/jiajunlong/TinyLLaVA-0.89B) | 50.38 | 36.37   | 50.02 | 65.44 | 1056.69 | 26.29 | 15.4   | **14.35 it/s** | **2 it/s** |
+