Update app.py

app.py

@@ -3,8 +3,7 @@ import gradio as gr
 
 
 def tokenize(input_text):
-    llama1_tokens = llama1_tokenizer(input_text, add_special_tokens=True)["input_ids"]
-    llama2_tokens = llama2_tokenizer(input_text, add_special_tokens=True)["input_ids"]
+    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"]
@@ -12,12 +11,11 @@ def tokenize(input_text):
     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-1: {len(llama1_tokens)}\nLLaMa-2: {len(llama2_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)}"
+    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__":
-    llama1_tokenizer = AutoTokenizer.from_pretrained("huggyllama/llama-7b")
-    llama2_tokenizer = AutoTokenizer.from_pretrained("TheBloke/Llama-2-7B-fp16")
+    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")