create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "mistralai/Codestral-22B-v0.1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def generate_text(prompt, max_length=1000, min_length=50, temperature=0.1):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(
+        inputs['input_ids'],
+        max_length=max_length,
+        min_length=min_length,
+        temperature=temperature
+    )
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+interface = gr.Interface(
+    fn=generate_text,
+    inputs=[
+        gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."),
+        gr.inputs.Slider(minimum=10, maximum=2000, default=1000, label="Max Length"),
+        gr.inputs.Slider(minimum=10, maximum=100, default=50, label="Min Length"),
+        gr.inputs.Slider(minimum=0.1, maximum=1, default=0.1, label="Temperature")
+    ],
+    outputs="text",
+    title="Text Generation with Mistralai",
+    description="Generate text using the mistralai/Codestral-22B-v0.1 model."
+)
+
+if __name__ == "__main__":
+    interface.launch()