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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() | |