add application file

app.py

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+import gradio as grad
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+def load_prompter():
+  prompter_model = AutoModelForCausalLM.from_pretrained("microsoft/Promptist")
+  tokenizer = AutoTokenizer.from_pretrained("gpt2")
+  tokenizer.pad_token = tokenizer.eos_token
+  tokenizer.padding_side = "left"
+  return prompter_model, tokenizer
+
+prompter_model, prompter_tokenizer = load_prompter()
+
+def generate(plain_text):
+    input_ids = prompter_tokenizer(plain_text.strip()+" Rephrase:", return_tensors="pt").input_ids
+    eos_id = prompter_tokenizer.eos_token_id
+    outputs = prompter_model.generate(input_ids, do_sample=False, max_new_tokens=75, num_beams=8, num_return_sequences=8, eos_token_id=eos_id, pad_token_id=eos_id, length_penalty=-1.0)
+    output_texts = prompter_tokenizer.batch_decode(outputs, skip_special_tokens=True)
+    res = output_texts[0].replace(plain_text+" Rephrase:", "").strip()
+    return res
+
+txt = grad.Textbox(lines=1, label="Initial Text", placeholder="Input Prompt")
+out = grad.Textbox(lines=1, label="Optimized Prompt")
+examples = ["A rabbit is wearing a space suit", "Several railroad tracks with one train passing by", "The roof is wet from the rain", "Cats dancing in a space club"]
+
+grad.Interface(fn=generate,
+               inputs=txt,
+               outputs=out,
+               title="Promptist Demo",
+               description="Promptist is a prompt interface for Stable Diffusion v1-4 (https://huggingface.co/CompVis/stable-diffusion-v1-4) that optimizes user input into model-preferred prompts. The online demo at Hugging Face Spaces is using CPU, so slow generation speed would be expected. Please load the model locally with GPUs for faster generation.",
+               examples=examples,
+               allow_flagging='never',
+               cache_examples=False,
+               theme="default").launch(enable_queue=True, debug=True)

requirements.txt

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+torch
+transformers==4.23.1
+pytorch_lightning==1.7.7