Init app

app.py

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+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import spaces
+
+# Set the model and tokenizer
+model_name = "meta-llama/Meta-Llama-3-70B-Instruct"
+lora_name = "Thermostatic/Llama-3-NeuralTranslate-Instructions-70b-v0.1-lora"
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+lora_adapter = model.load_adapter(lora_name, with_head=False)
+model.to('cuda')
+
+@spaces.GPU
+def translate(input_text):
+    input_ids = tokenizer.encode(f"Translate the following text from English to Spanish: {input_text}", return_tensors="pt")
+    response = model.generate(input_ids, adapter_name=lora_name, max_length=1024)
+    response_text = tokenizer.decode(response[0], skip_special_tokens=True)
+    return f"Translated text: {response_text}"
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        input_text = gr.Textbox(label="Enter a message to translate:")
+        submit = gr.Button("Translate")
+    output = gr.Textbox(label="Translated text:")
+
+    submit.click(fn=translate, inputs="input_text", outputs="output")
+
+demo.launch()