Spaces:
Sleeping
Sleeping
from transformers import AutoTokenizer | |
import gradio as gr | |
def formatarr(input): | |
return "["+",".join(str(x) for x in input)+"]" | |
def tokenize(input_text): | |
llama_tokens = llama_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
llama3_tokens = llama3_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"] | |
phi3_tokens = phi3_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
t5_tokens = t5_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
gemma_tokens = gemma_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
command_r_tokens = command_r_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
qwen_tokens = qwen_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
codeqwen_tokens = codeqwen_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
rwkv4_tokens = rwkv4_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
rwkv5_tokens = rwkv5_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
deepseek_tokens = deepseek_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
internlm_tokens = internlm_tokenizer(input_text, add_special_tokens=True)["input_ids"] | |
internlm2_tokens = internlm2_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-1/Phi-2": phi2_tokens, | |
"Phi-3": phi3_tokens, | |
"T5": t5_tokens, | |
"Gemma": gemma_tokens, | |
"Command-R": command_r_tokens, | |
"Qwen/Qwen1.5": qwen_tokens, | |
"CodeQwen": codeqwen_tokens, | |
"RWKV-v4": rwkv4_tokens, | |
"RWKV-v5/RWKV-v6": rwkv5_tokens, | |
"DeepSeek": deepseek_tokens, | |
"InternLM": internlm_tokens, | |
"InternLM2": internlm2_tokens | |
} | |
toks = "" | |
for model, tokens in results.items(): | |
toks += f"\n{model} gets {len(tokens)} tokens: {formatarr(tokens)}" | |
return toks | |
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("mistral-community/Mistral-7B-v0.2") | |
gpt2_tokenizer = AutoTokenizer.from_pretrained("openai-community/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") | |
phi3_tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct") | |
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") | |
qwen_tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen1.5-7B") | |
codeqwen_tokenizer = AutoTokenizer.from_pretrained("Qwen/CodeQwen1.5-7B") | |
rwkv4_tokenizer = AutoTokenizer.from_pretrained("RWKV/rwkv-4-14b-pile", trust_remote_code=True) | |
rwkv5_tokenizer = AutoTokenizer.from_pretrained("RWKV/v5-EagleX-v2-7B-HF", trust_remote_code=True) | |
deepseek_tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/DeepSeek-V2", trust_remote_code=True) | |
internlm_tokenizer = AutoTokenizer.from_pretrained("internlm/internlm-20b", trust_remote_code=True) | |
internlm2_tokenizer = AutoTokenizer.from_pretrained("internlm/internlm2-20b", trust_remote_code=True) | |
iface = gr.Interface( | |
fn=tokenize, inputs=gr.Textbox(label="Input Text", lines=19), outputs="text" | |
) | |
iface.launch() | |