Create APP.PY

APP.PY

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("yniw/open-calm-7b-4gib")
+model = AutoModelForCausalLM.from_pretrained("yniw/open-calm-7b-4gib")
+
+def generate_text(input_text, temperature=0.8, max_length=20):
+    input_ids = tokenizer.encode(input_text, return_tensors="pt")
+    output = model.generate(input_ids, max_length=max_length, temperature=temperature)
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+    return generated_text
+
+inputs = gr.inputs.Textbox(lines=2, label="Input Text")
+temperature = gr.inputs.Slider(minimum=0.2, maximum=1.0, default=0.8, step=0.1, label="Temperature")
+max_length = gr.inputs.Slider(minimum=10, maximum=50, default=20, step=5, label="Max Length")
+
+output_text = gr.outputs.Textbox(label="Generated Text")
+
+interface = gr.Interface(fn=generate_text, inputs=[inputs, temperature, max_length], outputs=output_text, title="Text Generation Interface")
+interface.launch()