Can't load tokenizer

[dannychantszfong]

I am attempting to load the Meta-LLaMA 3.3 70B Instruct model locally using the Hugging Face transformers library. While I have downloaded the required files, I am encountering an issue when trying to load the tokenizer.

My code:

from transformers import LlamaTokenizer, AutoModelForCausalLM
import torch

model_path = "G:\AI_models\models--meta-llama--Llama-3.3-70B-Instruct"

Load the tokenizer and model
tokenizer = LlamaTokenizer.from_pretrained(model_path, local_files_only=True)
model = AutoModelForCausalLM.from_pretrained(
model_path,
local_files_only=True,
torch_dtype=torch.float16,
device_map="auto"
)

Test the model
input_text = "Explain the benefits of artificial intelligence."
inputs = tokenizer(input_text, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=50)

output_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(output_text)

Error:

Traceback (most recent call last):
File "g:\Coding\AI\huggingface\llama3.3_70b\v1.py", line 7, in
tokenizer = LlamaTokenizer.from_pretrained(model_path, local_files_only=True)
File "C:\Users\ctz20\anaconda3\envs\rl_trading_bot\lib\site-packages\transformers\tokenization_utils_base.py", line 2020, in from_pretrained
raise EnvironmentError(
OSError: Can't load tokenizer for 'G:\AI_models\models--meta-llama--Llama-3.3-70B-Instruct'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'G:\AI_models\models--meta-llama--Llama-3.3-70B-Instruct' is the correct path to a
directory containing all relevant files for a LlamaTokenizer tokenizer.

Any Additional Context:
OS: Windows 10
Python: 3.9 (Conda environment)
Model Source: Hugging Face (Meta-LLaMA 3.3 70B Instruct)
transformers version: Latest (as of 2025-01-27)

What I Need Help With:
Why does the LlamaTokenizer fail to load the tokenizer files from the specified directory, despite all required files being present?
Is there a specific step I’m missing in configuring the tokenizer for this model?