Create app.py

app.py

@@ -0,0 +1,20 @@
+import gradio as gr
+from transformers import AutoTokenizer
+from transformers import AutoModelForCausalLM
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("Aityz/Aityz_model_eli5")
+
+model = AutoModelForCausalLM.from_pretrained("Aityz/Aityz_model_eli5")
+
+# maxtokens = int(input('What would you like the max tokens to be (default: 100) '))
+
+def aityz(input, maxtokens):
+    prompt = input
+    inputs = tokenizer(prompt, return_tensors="pt").input_ids
+    outputs = model.generate(inputs, max_new_tokens=maxtokens, do_sample=True, top_k=50, top_p=0.95)
+    output = tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    outputstr = ''.join(output)
+    return(outputstr)
+demo = gr.Interface(fn=aityz, inputs=["textbox", gr.Slider(1, 1000, value=100)], outputs="textbox")
+demo.launch() # enable share=True for Non Hugging Face Spaces Usage.........