Duplicate from Daniton/google-flan-t5-base

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README.md

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+---
+title: Google Flan T5 Base
+emoji: 🚀
+colorFrom: indigo
+colorTo: purple
+sdk: gradio
+sdk_version: 3.16.2
+app_file: app.py
+pinned: false
+duplicated_from: Daniton/google-flan-t5-base
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# load the pretrained model
+tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-base")
+model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")
+
+# define a predict function to generate text
+def generate_text(prompt):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+    generated_text = model.generate(input_ids, max_length=999999, top_p=0.9, top_k=40)
+    text = tokenizer.decode(generated_text[0], skip_special_tokens=True)
+    return text
+
+# create a Gradio interface for the text generator
+gr.Interface(fn=generate_text, inputs="text", outputs="text").launch()

requirements.txt

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+transformers
+torch