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Update README.md

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  1. README.md +3 -3
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@@ -3,7 +3,7 @@ language:
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  - en
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  datasets:
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  - liuhaotian/LLaVA-Instruct-150K
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- pipeline_tag: image-to-text
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  inference: false
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  arxiv: 2304.08485
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  license: llama2
@@ -50,7 +50,7 @@ pipe = pipeline("image-to-text", model=model_id)
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  url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"
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  image = Image.open(requests.get(url, stream=True).raw)
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- # Define a chat histiry and use `apply_chat_template` to get correctly formatted prompt
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  # Each value in "content" has to be a list of dicts with types ("text", "image")
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  conversation = [
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  {
@@ -89,7 +89,7 @@ model = LlavaForConditionalGeneration.from_pretrained(
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  processor = AutoProcessor.from_pretrained(model_id)
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- # Define a chat histiry and use `apply_chat_template` to get correctly formatted prompt
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  # Each value in "content" has to be a list of dicts with types ("text", "image")
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  conversation = [
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  {
 
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  - en
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  datasets:
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  - liuhaotian/LLaVA-Instruct-150K
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+ pipeline_tag: image-text-to-text
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  inference: false
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  arxiv: 2304.08485
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  license: llama2
 
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  url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"
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  image = Image.open(requests.get(url, stream=True).raw)
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+ # Define a chat history and use `apply_chat_template` to get correctly formatted prompt
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  # Each value in "content" has to be a list of dicts with types ("text", "image")
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  conversation = [
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  {
 
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  processor = AutoProcessor.from_pretrained(model_id)
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+ # Define a chat history and use `apply_chat_template` to get correctly formatted prompt
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  # Each value in "content" has to be a list of dicts with types ("text", "image")
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  conversation = [
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  {