Create README.md

README.md

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+#TinyLLaVA
+
+Here, we introduce TinyLLaVA-Qwen2-0.5B-siglip-so400m-patch14-384-base, which is trained by the TinyLLaVA Factory codebase. For LLM and vision tower, we choose Qwen2-0.5B and siglip-so400m-patch14-384, respectively. The dataset used for training this model is the LLaVA dataset.
+
+##Usage
+
+Execute the following test code:
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+hf_path = 'Zhang199/TinyLLaVA-Qwen2-0.5B-siglip-so400m-patch14-384-base'
+model = AutoModelForCausalLM.from_pretrained(hf_path, trust_remote_code=True)
+model.cuda()
+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="What are these?"
+image_url="http://images.cocodataset.org/test-stuff2017/000000000001.jpg"
+output_text, genertaion_time = model.chat(prompt=prompt, image=image_url, tokenizer=tokenizer)
+
+print('model output:', output_text)
+print('runing time:', genertaion_time)
+
+##Result