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| import gradio as gr | |
| import requests | |
| # GPT-J-6B API | |
| API_URL = "https://api-inference.huggingface.co/models/EleutherAI/gpt-j-6B" | |
| headers = {"Authorization": "Bearer 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"} | |
| prompt = """Oh, my life | |
| is changing every day | |
| Every possible way | |
| And oh, my dreams, | |
| it's never quite as it seems | |
| Never quite as it seems""" | |
| #examples = [["mind"], ["memory"], ["sleep"],["wellness"],["nutrition"]] | |
| def poem2_generate(word): | |
| p = word.lower() + "\n" + "poem using word: " | |
| gr.Markdown("Prompt is :{p}") | |
| json_ = {"inputs": p, | |
| "parameters": | |
| { | |
| "top_p": 0.9, | |
| "temperature": 1.1, | |
| "max_new_tokens": 50, | |
| "return_full_text": False | |
| }} | |
| response = requests.post(API_URL, headers=headers, json=json_) | |
| output = response.json() | |
| gr.Markdown("error? Reason is : {output}") | |
| output_tmp = output[0]['generated_text'] | |
| gr.Markdown("GPTJ response without splits is: {output_tmp}") | |
| poem = output[0]['generated_text'].split("\n\n")[0] # +"." | |
| if "\n\n" not in output_tmp: | |
| if output_tmp.find('.') != -1: | |
| idx = output_tmp.find('.') | |
| poem = output_tmp[:idx+1] | |
| else: | |
| idx = output_tmp.rfind('\n') | |
| poem = output_tmp[:idx] | |
| else: | |
| poem = output_tmp.split("\n\n")[0] # +"." | |
| poem = poem.replace('?','') | |
| gr.Markdown("Returned is: {poem}") | |
| return poem | |
| def poem_generate(word): | |
| p = prompt + word.lower() + "\n" + "poem using word: " | |
| gr.Markdown("Generate - Prompt is :{p}") | |
| json_ = {"inputs": p, | |
| "parameters": | |
| { | |
| "top_p": 0.9, | |
| "temperature": 1.1, | |
| "max_new_tokens": 50, | |
| "return_full_text": False | |
| }} | |
| response = requests.post(API_URL, headers=headers, json=json_) | |
| output = response.json() | |
| gr.Markdown("error? Reason is : {output}") | |
| output_tmp = output[0]['generated_text'] | |
| gr.Markdown("Response without splits is: {output_tmp}") | |
| poem = output[0]['generated_text'].split("\n\n")[0] # +"." | |
| if "\n\n" not in output_tmp: | |
| if output_tmp.find('.') != -1: | |
| idx = output_tmp.find('.') | |
| poem = output_tmp[:idx+1] | |
| else: | |
| idx = output_tmp.rfind('\n') | |
| poem = output_tmp[:idx] | |
| else: | |
| poem = output_tmp.split("\n\n")[0] # +"." | |
| poem = poem.replace('?','') | |
| gr.Markdown("Returned is: {poem}") | |
| return poem | |
| def poem_to_image(poem): | |
| gr.Markdown("toimage") | |
| poem = " ".join(poem.split('\n')) | |
| poem = poem + " oil on canvas." | |
| steps, width, height, images, diversity = '50','256','256','1',15 | |
| img = gr.Interface().load("spaces/multimodalart/latentdiffusion")(poem, steps, width, height, images, diversity)[0] | |
| return img | |
| def set_example(example: list) -> dict: | |
| return gr.Textbox.update(value=example[0]) | |
| demo = gr.Blocks() | |
| with demo: | |
| gr.Markdown("<h1><center>Few Shot Learning Text to Word Image Search</center></h1>") | |
| gr.Markdown("https://huggingface.co/blog/few-shot-learning-gpt-neo-and-inference-api, https://github.com/EleutherAI/the-pile") | |
| with gr.Row(): | |
| input_word = gr.Textbox(lines=7, value=prompt) | |
| poem_txt = gr.Textbox(lines=7) | |
| output_image = gr.Image(type="filepath", shape=(256,256)) | |
| b1 = gr.Button("Generate Text") | |
| b2 = gr.Button("Generate Image") | |
| b1.click(poem2_generate, input_word, poem_txt) | |
| b2.click(poem_to_image, poem_txt, output_image) | |
| examples=[["living, loving,"], ["I want to live. I want to give."],["Ive been to Hollywood. Ive been to Redwood"]] | |
| example_text = gr.Dataset(components=[input_word], samples=examples) | |
| example_text.click(fn=set_example,inputs = example_text,outputs= example_text.components) | |
| demo.launch(enable_queue=True, debug=True) |