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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", "ืืืจืื ืืืืจ", ""],
allow_flagging="never",
)
demo.queue()
demo.launch() |