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import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, TextGenerationPipeline
# Load the model and tokenizer
model = AutoModelForCausalLM.from_pretrained('cbauer/groupchatGPT', trust_remote_code=True, ignore_mismatched_sizes=True)
tokenizer = AutoTokenizer.from_pretrained('cbauer/groupchatGPT')
# Initialize the Text Generation pipeline
generator = TextGenerationPipeline(model=model, tokenizer=tokenizer)
def generate(text):
result = generator(text, max_length=30, num_return_sequences=1)
return result[0]["generated_text"]
examples = [
["###Chase Hello"],
["### Jake Whats up"],
]
demo = gr.Interface(
fn=generate,
inputs=gr.components.Textbox(lines=5, label="Input Text"),
outputs=gr.components.Textbox(label="Generated Text"),
examples=examples
)
demo.launch()
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