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Update app.py
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app.py
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@@ -12,9 +12,10 @@ else:
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tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-small")
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def generate(prompt, model_precision_type, max_new_tokens, repetition_penalty, temperature, top_p, top_k, seed):
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model = T5ForConditionalGeneration.from_pretrained("roborovski/superprompt-v1", device_map="auto", torch_dtype=model_precision_type)
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model.to(device)
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input_text = f"Expand the following prompt to add more detail: {prompt}"
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
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@@ -41,8 +42,6 @@ def generate(prompt, model_precision_type, max_new_tokens, repetition_penalty, t
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prompt = gr.Textbox(label="Prompt", interactive=True)
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model_precision_type = gr.Dropdown(choices=[('fp16', 'torch.float16'), ('fp32', 'torch.float32')], type="value", value='fp16', label="Model Precision", info="fp16 is faster, fp32 is more precise")
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max_new_tokens = gr.Slider(value=512, minimum=250, maximum=512, step=1, interactive=True, label="Max New Tokens", info="The maximum numbers of new tokens, controls how long is the output")
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repetition_penalty = gr.Slider(value=1.2, minimum=0, maximum=2, step=0.05, interactive=True, label="Repetition Penalty", info="Penalize repeated tokens, making the AI repeat less itself")
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@@ -56,12 +55,12 @@ top_k = gr.Slider(value=1, minimum=1, maximum=100, step=1, interactive=True, lab
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seed = gr.Number(value=42, interactive=True, label="Seed", info="A starting point to initiate the generation process, put 0 for a random one")
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examples = [
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["A storefront with 'Text to Image' written on it.",
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]
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gr.Interface(
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fn=generate,
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inputs=[prompt,
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outputs=gr.Textbox(label="Better Prompt"),
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title="SuperPrompt-v1",
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description='Make your prompts more detailed! <br> <a href="https://huggingface.co/roborovski/superprompt-v1">Model used</a> <br> <a href="https://brianfitzgerald.xyz/prompt-augmentation/">Model Blog</a> <br> Task Prefix: "Expand the following prompt to add more detail:" is already setted! <br> Hugging Face Space made by [Nick088](https://linktr.ee/Nick088)',
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tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-small")
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model = T5ForConditionalGeneration.from_pretrained("roborovski/superprompt-v1", device_map="auto", torch_dtype=auto)
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model.to(device)
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def generate(prompt, model_precision_type, max_new_tokens, repetition_penalty, temperature, top_p, top_k, seed):
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input_text = f"Expand the following prompt to add more detail: {prompt}"
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
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prompt = gr.Textbox(label="Prompt", interactive=True)
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max_new_tokens = gr.Slider(value=512, minimum=250, maximum=512, step=1, interactive=True, label="Max New Tokens", info="The maximum numbers of new tokens, controls how long is the output")
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repetition_penalty = gr.Slider(value=1.2, minimum=0, maximum=2, step=0.05, interactive=True, label="Repetition Penalty", info="Penalize repeated tokens, making the AI repeat less itself")
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seed = gr.Number(value=42, interactive=True, label="Seed", info="A starting point to initiate the generation process, put 0 for a random one")
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examples = [
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["A storefront with 'Text to Image' written on it.", 512, 1.2, 0.5, 1, 50, 42]
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]
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gr.Interface(
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fn=generate,
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inputs=[prompt, max_new_tokens, repetition_penalty, temperature, top_p, top_k, seed],
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outputs=gr.Textbox(label="Better Prompt"),
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title="SuperPrompt-v1",
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description='Make your prompts more detailed! <br> <a href="https://huggingface.co/roborovski/superprompt-v1">Model used</a> <br> <a href="https://brianfitzgerald.xyz/prompt-augmentation/">Model Blog</a> <br> Task Prefix: "Expand the following prompt to add more detail:" is already setted! <br> Hugging Face Space made by [Nick088](https://linktr.ee/Nick088)',
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