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Update README.md

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  1. README.md +6 -1
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@@ -6,7 +6,7 @@ tags:
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  - 'LLaMA '
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  - MultiModal
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  ---
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- *This is a Hugging Face friendly Model, the original can be found https://huggingface.co/liuhaotian/llava-llama-2-13b-chat-preview*
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  <br>
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  # LLaVA 13B Model Card
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@@ -50,16 +50,21 @@ usage is as follows
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  ```python
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  from transformers import LlavaProcessor, LlavaLlamaForCausalLM
 
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  PATH_TO_CONVERTED_WEIGHTS = "shauray/Llava-Llama-2-13B-hf"
 
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  model = LlavaLlamaForCausalLM.from_pretrained(PATH_TO_CONVERTED_WEIGHTS)
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  processor = LlavaProcessor.from_pretrained(PATH_TO_CONVERTED_TOKENIZER)
 
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  url = "https://llava-vl.github.io/static/images/view.jpg"
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  image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
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  prompt = "How would you best describe the image given?"
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  inputs = processor(text=prompt, images=image, return_tensors="pt")
 
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  # Generate
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  generate_ids = model.generate(**inputs, max_length=30)
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  tokenizer.batch_decode(generate_ids, skip_special_tokens=True)[0]
 
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  """The photograph shows a wooden dock floating on the water, with mountains in the background. It is an idyllic scene that captures both
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  nature and human-made structures at their finest moments of beauty or tranquility depending upon one's perspective as they gaze into it"""
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  ```
 
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  - 'LLaMA '
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  - MultiModal
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  ---
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+ *This is a Hugging Face friendly Model, the original can be found at https://huggingface.co/liuhaotian/llava-llama-2-13b-chat-preview*
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  <br>
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  # LLaVA 13B Model Card
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  ```python
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  from transformers import LlavaProcessor, LlavaLlamaForCausalLM
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+
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  PATH_TO_CONVERTED_WEIGHTS = "shauray/Llava-Llama-2-13B-hf"
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+
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  model = LlavaLlamaForCausalLM.from_pretrained(PATH_TO_CONVERTED_WEIGHTS)
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  processor = LlavaProcessor.from_pretrained(PATH_TO_CONVERTED_TOKENIZER)
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+
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  url = "https://llava-vl.github.io/static/images/view.jpg"
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  image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
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  prompt = "How would you best describe the image given?"
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  inputs = processor(text=prompt, images=image, return_tensors="pt")
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+
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  # Generate
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  generate_ids = model.generate(**inputs, max_length=30)
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  tokenizer.batch_decode(generate_ids, skip_special_tokens=True)[0]
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+
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  """The photograph shows a wooden dock floating on the water, with mountains in the background. It is an idyllic scene that captures both
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  nature and human-made structures at their finest moments of beauty or tranquility depending upon one's perspective as they gaze into it"""
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  ```