hitchhiker3010 commited on
Commit
20b3af9
1 Parent(s): edba557

Add application and requirements files

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Files changed (2) hide show
  1. app.py +33 -0
  2. requirements.txt +2 -0
app.py ADDED
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+ import gradio as gr
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+ from transformers import AutoTokenizer
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+ from huggingface_hub import repo_exists
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+
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+ def token_viz(model_name, text):
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+ if not repo_exists(model_name):
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+ gr.Error(f"{model_name} is not a valid HF repo. Please enter a valid repo.")
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+ tokenizer = AutoTokenizer.from_pretrained(model_name,cache_dir=f"./.cache/hf/{model_name}")
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+ print(model_name,text)
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+ tokens = tokenizer.encode(text)
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+ return [(tokenizer.decode(token).replace("\n",r"\n"), str(token)) for token in tokens]
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+
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+
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+ MARKDOWN = """
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+ <h1 style='text-align: center; margin-bottom: 1rem'><div align="center">Token Visualizer ⚔️</div></h1>
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+
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+ Enter the Tokenizer you want to use to visualize the tokens.
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+
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+ Example: To use <https://huggingface.co/Qwen/Qwen2-72B-Instruct> model's tokenizer just enter **Qwen/Qwen2-72B-Instruct**
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+ """
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+
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+
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+ with gr.Blocks() as demo:
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+ gr.Markdown(MARKDOWN)
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+ with gr.Row():
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+ model_name = gr.Textbox(label="repo_name",interactive=True,placeholder="Enter the HF model here...")
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+ text = gr.Textbox(label="text",interactive=True, placeholder="Enter the text to be tokenized")
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+ output1 = gr.HighlightedText(show_inline_category=True)
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+
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+ btn = gr.Button("Run")
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+ btn.click(token_viz, inputs=[model_name, text], outputs=[output1])
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+
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+ demo.queue().launch()
requirements.txt ADDED
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+ transformers==4.42.4
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+ huggingface-hub===0.23.4