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README.md
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#
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Author: Pau Rodriguez Inserte (@pauri32)
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## Setup and running instructions
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## Reasoning of the LLM design choices
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### Model selected: BloomZ
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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
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