Add application file

app.py

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+from aitextgen import aitextgen
+import gradio as gr
+import os
+from transformers import pipeline
+from gradio import inputs
+from gradio.inputs import Textbox
+from gradio import outputs
+
+
+ai=aitextgen(model='EleutherAI/gpt-neo-2.7B',to_gpu=False) # EleutherAI/gpt-neo-2.7B EleutherAI/gpt-neo-1.3B
+# ai=aitextgen(model='EleutherAI/gpt-neo-1.3B',to_gpu=False)
+
+def ai_text(Input):
+  generated_text = ai.generate_one(max_length = 1000, prompt = Input, no_repeat_ngram_size = 3) #repetition_penalty = 1.9)
+  #print(type(generated_text))
+  return generated_text
+
+
+title_ = "AI Long Content Generation"
+description_ = "Converts short sentences into 1000 words"
+output_text = gr.outputs.Textbox()
+iface=gr.Interface(ai_text,"textbox", output_text, title=title_,description=description_)#.launch()
+iface.launch()
+
+
+
+#HF_TOKEN = os.environ.get("HF_TOKEN") 
+#generator2 = gr.Interface.load("huggingface/EleutherAI/gpt-neo-2.7B", api_key=HF_TOKEN) # add api_key=HF_TOKEN to get over the quota error
+#generator3 = gr.Interface.load("huggingface/EleutherAI/gpt-j-6B", api_key=HF_TOKEN)
+#generator1 = gr.Interface.load("huggingface/gpt2-large", api_key=HF_TOKEN)
+#gr.Parallel(generator1, generator2, generator3, inputs=gr.inputs.Textbox(lines=5, label="Enter a sentence to get another sentence."),
+#            title=title, examples=examples).launch(share=False)

requirements.txt

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+aitextgen
+gradio