first

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
+
+def generate(text):
+	input_ids = tokenizer(text, return_tensors="pt").input_ids
+	gen_tokens = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=100)
+	return tokenizer.batch_decode(gen_tokens)[0]
+
+gradio_ui = gr.Interface(fn=generate, title="Use GPT-J:", description="Put your text into the box below, and have the GPT-J open source model generate the next 100 characters!", inputs=gr.inputs.Textbox(label="Put your text here!"), outputs=gr.inputs.Textbox(label="Your text:"))
+gradio_ui.launch()
+
+
+
+
+

flagged/log.csv

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+name,output,flag,username,timestamp
+Hello,Hello Hello!!,,,2023-03-22 16:51:10.476201

requirements.txt

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+gradio
+transformers
+torch