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import gradio as gr |
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import requests |
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API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B" |
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prompt = """ |
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word: risk |
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poem using word: And then the day came, |
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when the risk |
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to remain tight |
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in a bud |
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was more painful |
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than the risk |
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it took |
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to blossom. |
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word: """ |
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examples = [["river"], ["night"], ["trees"],["table"],["laughs"]] |
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def poem_generate(word): |
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p = prompt + word.lower() + "\n" + "poem using word: " |
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print(f"Prompt is :{p}") |
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json_ = {"inputs": p, |
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"parameters": |
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{ |
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"top_p": 0.9, |
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"temperature": 1.1, |
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"max_new_tokens": 50, |
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"return_full_text": False |
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}} |
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response = requests.post(API_URL, json=json_) |
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output = response.json() |
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print(f"Poem without splits is: {output[0]['generated_text']}") |
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poem = output[0]['generated_text'].split("\n\n")[0] |
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return poem |
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def poem_to_image(poem): |
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print(poem) |
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poem = " ".join(poem.split('\n')) |
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poem = poem + " oil on canvas." |
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steps, width, height, images, diversity = '50','256','256','1',15 |
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img = gr.Interface.load("spaces/multimodalart/latentdiffusion")(poem, steps, width, height, images, diversity)[0] |
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return img |
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demo = gr.Blocks() |
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with demo: |
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gr.Markdown("<h1><center>Generate Short Poem along with an Illustration</center></h1>") |
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gr.Markdown( |
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"<div>Enter a single word you would want GPTJ-6B to write Poetry 🎤 on.</div>" |
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"<div>Generate an illustration 🎨 provided by Latent Diffusion model.</div><div>GPJ-6B is a 6 Billion parameter autoregressive language model. It generates the Poem based on how it has been 'prompt-engineered' 🤗 The complete text of generated poem then goes in as a prompt to the amazing Latent Diffusion Art space by <a href='https://huggingface.co/spaces/multimodalart/latentdiffusion' target='_blank'>Multimodalart</a>.</div>Please note that some of the Poems/Illustrations might not look at par, and well, this is what happens when you can't 'cherry-pick' and post 😁" |
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) |
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with gr.Row(): |
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input_word = gr.Textbox(placeholder="Enter a word here to create a Poem on..") |
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poem_txt = gr.Textbox(lines=7) |
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output_image = gr.Image(type="filepath", shape=(256,256)) |
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b1 = gr.Button("Generate Poem") |
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b2 = gr.Button("Generate Image") |
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b1.click(poem_generate, input_word, poem_txt) |
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b2.click(poem_to_image, poem_txt, output_image) |
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examples=examples |
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demo.launch(enable_queue=True, debug=True) |
