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from transformers import AutoTokenizer
import gradio as gr
gpt2_tokenizer = AutoTokenizer.from_pretrained("gpt2")
gpt_neox_tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neox-20b")
llama_tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/llama-tokenizer")
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")
mistral_tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
def tokenize(input_text):
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"]
llama_tokens = llama_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"]
mistral_tokens = mistral_tokenizer(input_text, add_special_tokens=True)["input_ids"]
return f"GPT-2/GPT-J: {len(gpt2_tokens)}\nGPT-NeoX: {len(gpt_neox_tokens)}\nLLaMa: {len(llama_tokens)}\nFalcon: {len(falcon_tokens)}\nPhi-2: {len(phi2_tokens)}\nT5: {len(t5_tokens)}\nMistral: {len(mistral_tokens)}"
iface = gr.Interface(fn=tokenize, inputs=gr.Textbox(lines=7), outputs="text")
iface.launch() |