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@@ -7,11 +7,19 @@ sdk: docker
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  pinned: false
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  ---
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- # LanguageWire Technical challenge
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  Author: Pau Rodriguez Inserte (@pauri32)
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  ## Setup and running instructions
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- TODO
 
 
 
 
 
 
 
 
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  ## Reasoning of the LLM design choices
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  ### Model selected: BloomZ
 
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  pinned: false
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  ---
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+ # Technical challenge
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  Author: Pau Rodriguez Inserte (@pauri32)
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  ## Setup and running instructions
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+ You have two options to run the challenge!
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+ ### HuggingFace Space
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+ 1. Just click on the 'App' tab of the HuggingFace space.
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+ 2. Use FastAPI's interactive Swagger UI
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+ 3. Go to ```/language-detection``` endpoint and introduce an input text to identify its language (only available English, French and Spanish)
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+ 4. Go to ```/entity-recognition``` endpoint and introduce an input text to retrieve and count locations, people and organizations named-entities.
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+ ### Download Docker image
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+ 1. You can run it locally by using the following command ```docker run -it -p 7860:7860 --platform=linux/amd64 registry.hf.space/pauri32-llm-challenge:latest```
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+ 2. By opening ```localhost:7860``` in your browser, you will be able to interact with FastAPI's UI.
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  ## Reasoning of the LLM design choices
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  ### Model selected: BloomZ