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()