Create app.py

app.py

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+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import gradio as gr
+
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B")
+model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
+
+def text_generation(input_text, seed):
+  input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+  torch.manual_seed(seed) # Max value: 18446744073709551615
+  outputs = model.generate(input_ids, do_sample=True, min_length=50, max_length=200)
+  generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+  return generated_text
+
+title = "Text Generator Demo GPT-Neo"
+description = "Text Generator Application by ecarbo"
+
+gr.Interface(
+    text_generation,
+    [gr.inputs.Textbox(lines=2, label="Enter input text"), gr.inputs.Number(default=10, label="Enter seed number")],
+    [gr.outputs.Textbox(type="auto", label="Text Generated")],
+    title=title,
+    description=description,
+    theme="huggingface"
+).launch()