bilgeyucel commited on
Commit
e833e6f
1 Parent(s): 102b698

Update app.py

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Files changed (1) hide show
  1. app.py +5 -2
app.py CHANGED
@@ -5,6 +5,7 @@ from haystack.components.generators import HuggingFaceTGIGenerator
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  from haystack.components.builders.prompt_builder import PromptBuilder
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  from haystack import Pipeline
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  from haystack.utils import Secret
 
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  from image_captioner import ImageCaptioner
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  description = """
@@ -15,7 +16,9 @@ description = """
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  * Choose your model
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  * ✨ Captionate! ✨
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- `mistralai/Mistral-7B-Instruct-v0.2` performs best, but try different models to see how they react to the same prompt.
 
 
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  Built by [Bilge Yucel](https://twitter.com/bilgeycl) using [Haystack 2.0](https://github.com/deepset-ai/haystack) 💙
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  """
@@ -32,7 +35,7 @@ hf_api_key = os.environ["HF_API_KEY"]
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  def generate_caption(image_file_path, model_name):
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  image_to_text = ImageCaptioner(
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- model_name="nlpconnect/vit-gpt2-image-captioning",
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  )
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  prompt_builder = PromptBuilder(template=prompt_template)
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  generator = HuggingFaceTGIGenerator(model=model_name, token=Secret.from_token(hf_api_key), generation_kwargs={"max_new_tokens":50})
 
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  from haystack.components.builders.prompt_builder import PromptBuilder
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  from haystack import Pipeline
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  from haystack.utils import Secret
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+
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  from image_captioner import ImageCaptioner
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  description = """
 
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  * Choose your model
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  * ✨ Captionate! ✨
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+ It uses [Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base) model for image2task caption generation task.
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+
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+ For Instagrammable captions, `mistralai/Mistral-7B-Instruct-v0.2` performs best, but try different models to see how they react to the same prompt.
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  Built by [Bilge Yucel](https://twitter.com/bilgeycl) using [Haystack 2.0](https://github.com/deepset-ai/haystack) 💙
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  """
 
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  def generate_caption(image_file_path, model_name):
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  image_to_text = ImageCaptioner(
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+ model_name="Salesforce/blip-image-captioning-base",
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  )
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  prompt_builder = PromptBuilder(template=prompt_template)
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  generator = HuggingFaceTGIGenerator(model=model_name, token=Secret.from_token(hf_api_key), generation_kwargs={"max_new_tokens":50})