Bsbell21 commited on
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8c7f3ae
1 Parent(s): 14b1471

Create app.py

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  1. app.py +45 -0
app.py ADDED
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+ import torch
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+ from peft import PeftModel, PeftConfig
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ peft_model_id = f"Bsbell21/GenerAd-AI-BLOOMZ"
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+ config = PeftConfig.from_pretrained(peft_model_id)
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+ model = AutoModelForCausalLM.from_pretrained(
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+ config.base_model_name_or_path,
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+ return_dict=True,
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+ device_map="auto"
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
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+
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+ # Load the Lora model
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+ model = PeftModel.from_pretrained(model, peft_model_id)
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+
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+
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+ def make_inference(product_name, product_description):
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+ batch = tokenizer(
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+ f"### Product and Description:\n{product_name}: {product_description}\n\n### Ad:",
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+ return_tensors="pt",
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+ )
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+
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+ batch = {key: value.to('cuda:0') for key, value in batch.items()}
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+
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+ with torch.cuda.amp.autocast():
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+ output_tokens = model.generate(**batch, max_new_tokens=50)
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+
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+ return tokenizer.decode(output_tokens[0], skip_special_tokens=True)
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+
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+
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+ if __name__ == "__main__":
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+ # make a gradio interface
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+ import gradio as gr
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+
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+ gr.Interface(
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+ make_inference,
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+ [
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+ gr.Textbox(lines=2, label="Product Name"),
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+ gr.Textbox(lines=5, label="Product Description"),
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+ ],
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+ gr.Textbox(label="Ad"),
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+ title="GenerAd-AI",
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+ description="GenerAd-AI is a generative model that generates ads for products.",
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+ ).launch()