Create app.py

app.py

@@ -0,0 +1,26 @@
+import gradio as gr
+from peft import get_peft_config, get_peft_model, PeftModel, PeftConfig, LoraConfig, TaskType
+
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# huggingface hub model id
+model_id="xavierbarbier/flan-t5-small-ameli_qa_10k"
+
+
+# load model from the hub
+model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+max_target_length = 512
+
+def greet(input_text):
+  input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+  outputs = model.generate(input_ids = input_ids, max_length = max_target_length)
+  answer = tokenizer.decode(outputs[0]).replace("<pad> ","").replace("</s>","")
+
+  return answer
+
+iface = gr.Interface(fn=greet, inputs=["text"],
+                     outputs="text")
+iface.launch(share=True)