WebTokenizer / app.py
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from transformers import AutoTokenizer
import gradio as gr
gpt2_tokenizer = AutoTokenizer.from_pretrained("gpt2")
gptj_tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6b")
gpt_neox_tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neox-20b")
llama_tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/llama-tokenizer")
def tokenize(input_text):
gpt2_tokens = gpt2_tokenizer(input_text)["input_ids"]
gptj_tokens = gptj_tokenizer(input_text)["input_ids"]
gpt_neox_tokens = gpt_neox_tokenizer(input_text)["input_ids"]
llama_tokens = llama_tokenizer(input_text)["input_ids"]
return f"""Number of tokens.
GPT-2: {len(gpt2_tokens)}
GPT-J: {len(gptj_tokens)}
GPT-NeoX: {len(gpt_neox_tokens)}
LLaMa: {len(llama_tokens)}
"""
iface = gr.Interface(fn=tokenize, inputs=gr.inputs.Textbox(lines=7), outputs="text")
iface.launch()