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app.py
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@@ -4,7 +4,7 @@ app.py
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This script creates a graphical interface to test an automatic evaluation generation model.
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The model is available on Hugging Face and is based on the Llama 3.2 3B-instruct model.
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model_id: "eltorio/Llama-3.
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Author: Ronan Le Meillat
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License: AGPL-3.0
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@@ -19,8 +19,8 @@ if os.environ.get('HF_TOKEN') is None:
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raise ValueError("You must set the HF_TOKEN environment variable to use this script, you also need to have access to the Llama 3.2 model family")
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# sets the main paremeters
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hugging_face_model_id = "eltorio/Llama-3.
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base_model_path = "meta-llama/Llama-3.
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device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
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# Define the title, description, and device description for the Gradio interface
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@@ -29,7 +29,7 @@ title = f"Une intelligence artificielle pour écrire des appréciations qui tour
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desc = "Ce modèle vous propose une évaluation automatique."
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# Define the long description for the Gradio interface
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long_desc = f"Cette démonstration est basée sur le modèle <a href='https://huggingface.co/eltorio/Llama-3.
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# Load the model
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processor = AutoProcessor.from_pretrained(
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@@ -73,7 +73,7 @@ def infere(trimestre: str, moyenne_1: float,moyenne_2: float,moyenne_3: float, c
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gr.Warning("""No GPU available.<br>
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The answer will appear in around 10 minutes!<br>
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But it takes only a few seconds on a decent GPU.<br>
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Open a message in the <a href='https://huggingface.co/spaces/eltorio/Llama-3.
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""",
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duration=500)
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messages = get_conversation(trimestre, moyenne_1, moyenne_2, moyenne_3, comportement, participation, travail)
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This script creates a graphical interface to test an automatic evaluation generation model.
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The model is available on Hugging Face and is based on the Llama 3.2 3B-instruct model.
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model_id: "eltorio/Llama-3.1-8B-appreciation"
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Author: Ronan Le Meillat
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License: AGPL-3.0
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raise ValueError("You must set the HF_TOKEN environment variable to use this script, you also need to have access to the Llama 3.2 model family")
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# sets the main paremeters
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hugging_face_model_id = "eltorio/Llama-3.1-8B-appreciation"
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base_model_path = "meta-llama/Llama-3.1-8B"
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device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
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# Define the title, description, and device description for the Gradio interface
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desc = "Ce modèle vous propose une évaluation automatique."
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# Define the long description for the Gradio interface
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long_desc = f"Cette démonstration est basée sur le modèle <a href='https://huggingface.co/eltorio/Llama-3.1-8B-appreciation'>Llama-3.1-8B-appreciation</a>, c'est un LLM développé à l'aide de Llama 3.2 3B-instruct!<br><b>{device_desc}</b><br> 2024 - Ronan Le Meillat"
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# Load the model
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processor = AutoProcessor.from_pretrained(
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gr.Warning("""No GPU available.<br>
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The answer will appear in around 10 minutes!<br>
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But it takes only a few seconds on a decent GPU.<br>
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Open a message in the <a href='https://huggingface.co/spaces/eltorio/Llama-3.1-8B-appreciation/discussions'>Community Discussion</a>.<br>
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""",
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duration=500)
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messages = get_conversation(trimestre, moyenne_1, moyenne_2, moyenne_3, comportement, participation, travail)
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