Create app.py

New files added

app.py

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+import gradio as gr
+from unsloth import FastLanguageModel
+
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name = "muzammil-eds/Meta-Llama-3.1-8B-Instruct-English-to-French-v2",
+    dtype = None,
+    load_in_4bit = True,
+)
+FastLanguageModel.for_inference(model)
+
+def process_input(model, tokenizer,  input_text):
+    prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Instruction:
+Translate the following English text to French.
+
+### Input:
+{}
+
+### Response:
+"""
+
+    formatted_prompt = prompt.format( input_text)
+    inputs = tokenizer([formatted_prompt], return_tensors="pt").to("cuda")
+    outputs = model.generate(**inputs, max_new_tokens=512, use_cache=True)
+    decoded_output = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
+    response_start = "### Response:"
+    response = decoded_output.split(response_start)[-1].strip()
+
+    return response
+
+
+
+
+# Define the Gradio interface
+def gradio_app(input_text):
+    output = process_input(model, tokenizer,  input_text)
+    return output
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=gradio_app,
+    inputs=gr.Textbox(label="Enter your input text"),
+    outputs=gr.Textbox(label="Generated Output"),
+    title="Text to Response Generator",
+    description="Enter input text and get a response."
+)
+
+interface.launch()