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import gradio as gr |
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API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B" |
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def poem_generate(word): |
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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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prompt = prompt + word + "\n" + "poem using word: " |
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json_ = {"inputs": prompt, |
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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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poem = output[0]['generated_text'].spilt("\n\n")[0] +"." |
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return poem |
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def poem_to_image(poem): |
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poem = " ".join(poem[1:].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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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") |
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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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demo.launch(enable_queue=True, debug=True) |
