Update app.py
Browse files
app.py
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@@ -1,4 +1,4 @@
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import
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from transformers import AutoModelForCausalLM, AutoTokenizer
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# Charger le modèle et le tokenizer
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@@ -6,10 +6,15 @@ model_name = "Rimyy/MISTRAL-finetuneGSMdata1exp"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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def predict(prompt):
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(inputs.input_ids, max_length=256)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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import streamlit as st
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from transformers import AutoModelForCausalLM, AutoTokenizer
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# Charger le modèle et le tokenizer
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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# Fonction de prédiction
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def predict(prompt):
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(inputs.input_ids, max_length=256)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Interface utilisateur Streamlit
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st.title("Modèle de génération de texte")
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prompt = st.text_area("Entrez votre texte:")
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if st.button("Générer"):
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result = predict(prompt)
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st.text_area("Résultat", value=result, height=200)
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