Initial commit

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer
+model_name = "ruggsea/gpt-ita-fdi_lega"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Define the text completion function
+def complete_tweet(initial_text, temperature=0.7, top_k=50, top_p=0.92, repetition_penalty=1.2):
+    # Tokenize the input text
+    input_ids = tokenizer.encode(initial_text, return_tensors="pt")
+
+    # Generate text using the model with custom parameters
+    output = model.generate(
+        input_ids,
+        max_length=140,
+        do_sample=True,
+        temperature=temperature,
+        top_k=top_k,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty
+    )
+
+    # Decode the generated output
+    completed_text = tokenizer.decode(output[0], skip_special_tokens=True)
+
+    return completed_text
+
+# Create the Gradio interface with a multiline textbox for input and output
+tweet_input_output = gr.Textbox(
+    label="Scrivi l'inizio del tweet e premi 'Submit' per completare il tweet",
+    type="text"
+)
+interface = gr.Interface(
+    fn=complete_tweet,
+    inputs=tweet_input_output,
+    outputs=tweet_input_output,
+    live=False,
+    examples=[["I migranti"], ["Il ddl Zan"]],
+    title="Twitta come un parlamentare di FDI/Lega"
+)
+
+# Start the Gradio interface
+interface.launch(share=True)