app.py

import gradio as gr
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import spaces

title = "Fakypedia"

DESCRIPTION = """\
# Genarate a silly article
A bilingual (English and Hebrew) [nonsense generation model](https://huggingface.co/Norod78/SmolLM-135M-FakyPedia-EngHeb) which produces silly Wikipedia-like abstract text.  
Tap on the \"Submit\" button to generate a silly and/or fake \"Wikipedia-Like\" article based on the input title
"""

article = "<p>This model extended the tokenizer of and is a fine-tuned of [SmolLM-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-135M-Instruct)</p>"

CUDA_AVAILABLE = torch.cuda.is_available()
device = torch.device("cuda" if CUDA_AVAILABLE else "cpu")

model_id = "Norod78/SmolLM-135M-FakyPedia-EngHeb"
tokenizer = AutoTokenizer.from_pretrained(model_id)
tokenizer.pad_token_id = tokenizer.eos_token_id
bos_token = tokenizer.bos_token
model = AutoModelForCausalLM.from_pretrained(model_id).to(device)
model.generation_config.pad_token_id = tokenizer.pad_token_id

torch.manual_seed(1234)

@spaces.GPU
def generate_fakypedia(article_title: str):
    with torch.no_grad():
        result = ""
        string_to_tokenize= f"{bos_token}\\%{article_title}"
        input_ids = tokenizer( string_to_tokenize, return_tensors="pt").input_ids.to(device)        
        sample_outputs = model.generate(input_ids, do_sample=True,repetition_penalty=1.2, temperature=0.5, max_length=96, num_return_sequences=3)        
        if article_title == None or len(article_title) == 0:
            result += f"# Fakypedia results with random titles  \n"
            article_title = ""
        else:
            result += f"# Fakypedia results for \"{article_title}\"  \n"
        for i, sample_output in enumerate(sample_outputs):
            decoded_output = tokenizer.decode(sample_output, skip_special_tokens=True)
            decoded_output = decoded_output.replace(f"\%{article_title}", f"## {article_title}").replace("\%", " ").replace("\\n", "  \n")
            decoded_output = decoded_output.replace("##   \n", "\n")
            result += "{}\n".format(decoded_output)
        return result

demo = gr.Interface(
    generate_fakypedia,    
    inputs=gr.Textbox(lines=1, label="Enter a title for the article (or leave blank for a random one)"),
    outputs=gr.Markdown(label="Generated fakypedia article"),
    title=title,
    description=DESCRIPTION,
    article=article,
    examples=["Hugging face", "A socially awkward potato", "דורון אדלר", ""],
    allow_flagging="never",
)

demo.queue()
demo.launch()