Upload app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained("K-GPT_NEO125M")
+
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125M")
+
+model = AutoModelForCausalLM.from_pretrained("K-GPT_NEO125M")
+
+def get_gen(sample: str, returns: int=1, length: int=50):
+    input_ids = tokenizer(sample, return_tensors='pt').input_ids
+    output = model.generate(input_ids, 
+        max_length = length, 
+        num_beams = 5,
+        no_repeat_ngram_size  = 3,
+        early_stopping = True,
+        do_sample=True,
+        num_return_sequences = returns,
+        pad_token_id=tokenizer.eos_token_id
+    )
+    generation = tokenizer.batch_decode(output, skip_special_tokens=True)
+    return generation[0]
+
+with gr.Blocks() as demo:
+    textbox = gr.Textbox(placeholder="Type here and press enter...", lines=4)
+    btn = gr.Button("Generate")
+    btn.click(get_gen, textbox, textbox)
+
+demo.launch(share=False)