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from transformers import AutoTokenizer | |
import gradio as gr | |
def tokenize(input_text): | |
llama_tokens = len( | |
llama_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
) | |
llama3_tokens = len( | |
llama3_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
) | |
mistral_tokens = len( | |
mistral_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
) | |
gpt2_tokens = len(gpt2_tokenizer(input_text, add_special_tokens=True)["input_ids"]) | |
gpt_neox_tokens = len( | |
gpt_neox_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
) | |
falcon_tokens = len( | |
falcon_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
) | |
phi2_tokens = len(phi2_tokenizer(input_text, add_special_tokens=True)["input_ids"]) | |
t5_tokens = len(t5_tokenizer(input_text, add_special_tokens=True)["input_ids"]) | |
gemma_tokens = len(gemma_tokenizer(input_text, add_special_tokens=True)["input_ids"]) | |
command_r_tokens = len(command_r_tokenizer(input_text, add_special_tokens=True)["input_ids"]) | |
results = { | |
"LLaMa-1/LLaMa-2": llama_tokens, | |
" LLaMa-3": llama3_tokens, | |
" Mistral": mistral_tokens, | |
" GPT-2/GPT-J": gpt2_tokens, | |
" GPT-NeoX": gpt_neox_tokens, | |
" Falcon": falcon_tokens, | |
" Phi": phi2_tokens, | |
" T5": t5_tokens, | |
" Gemma": gemma_tokens, | |
" Command-R": command_r_tokens | |
} | |
# Sort the results in descending order based on token length | |
sorted_results = sorted(results.items(), key=lambda x: x[1], reverse=True) | |
return "\n".join([f"{model}: {tokens}" for model, tokens in sorted_results]) | |
if __name__ == "__main__": | |
llama_tokenizer = AutoTokenizer.from_pretrained("TheBloke/Llama-2-7B-fp16") | |
llama3_tokenizer = AutoTokenizer.from_pretrained("unsloth/llama-3-8b") | |
mistral_tokenizer = AutoTokenizer.from_pretrained("unsloth/Mistral-7B-v0.2") | |
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") | |
gemma_tokenizer = AutoTokenizer.from_pretrained("alpindale/gemma-2b") | |
command_r_tokenizer = AutoTokenizer.from_pretrained("CohereForAI/c4ai-command-r-plus") | |
iface = gr.Interface(fn=tokenize, inputs=gr.Textbox(lines=10), outputs="text") | |
iface.launch() | |