WebTokenizer / app.py
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from transformers import AutoTokenizer
import gradio as gr
def tokenize(input_text):
llama_tokens = llama2_tokenizer(input_text, add_special_tokens=True)["input_ids"]
mistral_tokens = mistral_tokenizer(input_text, add_special_tokens=True)["input_ids"]
gpt2_tokens = gpt2_tokenizer(input_text, add_special_tokens=True)["input_ids"]
gpt_neox_tokens = gpt_neox_tokenizer(input_text, add_special_tokens=True)["input_ids"]
falcon_tokens = falcon_tokenizer(input_text, add_special_tokens=True)["input_ids"]
phi2_tokens = phi2_tokenizer(input_text, add_special_tokens=True)["input_ids"]
t5_tokens = t5_tokenizer(input_text, add_special_tokens=True)["input_ids"]
return f"LLaMa: {len(llama1_tokens)}\nMistral: {len(mistral_tokens)}\nGPT-2/GPT-J: {len(gpt2_tokens)}\nGPT-NeoX: {len(gpt_neox_tokens)}\nFalcon: {len(falcon_tokens)}\nPhi-2: {len(phi2_tokens)}\nT5: {len(t5_tokens)}"
if __name__ == "__main__":
llama_tokenizer = AutoTokenizer.from_pretrained("TheBloke/Llama-2-7B-fp16")
mistral_tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
gpt2_tokenizer = AutoTokenizer.from_pretrained("gpt2")
gpt_neox_tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neox-20b")
falcon_tokenizer = AutoTokenizer.from_pretrained("tiiuae/falcon-7b")
phi2_tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2")
t5_tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-xxl")
iface = gr.Interface(fn=tokenize, inputs=gr.Textbox(lines=7), outputs="text")
iface.launch()