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@@ -19,19 +19,8 @@ This model has the potential to produce unusual or unexpected results, due to th
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  **How to use:**
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- You can use this model by providing a product or brand name as an input. For example,
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- ```
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- from transformers import GPT2LMHeadModel, GPT2Tokenizer
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-
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- tokenizer = GPT2Tokenizer.from_pretrained("PeterBrendan/AdsGPT2")
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- model = GPT2LMHeadModel.from_pretrained("PeterBrendan/AdsGPT2")
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-
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- inputs = tokenizer("Nike Basketball", return_tensors="pt")
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- outputs = model.generate(**inputs, max_length=100)
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-
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- print(tokenizer.decode(outputs[0]))
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- ```
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  **Training data:**
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  This model was trained on a dataset consisting of over 10,000 programmatic ad creatives, which included a variety of different product and brand advertisements. The data was collected from various ad platforms and represents a wide range of ad styles and formats.
 
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  **How to use:**
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+ You can use this model by providing a product or brand name as an input. For example: *Nike Air Force Ones*
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  **Training data:**
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  This model was trained on a dataset consisting of over 10,000 programmatic ad creatives, which included a variety of different product and brand advertisements. The data was collected from various ad platforms and represents a wide range of ad styles and formats.