I’m struggling to replicate the results from this repository but using other LLMs such as LLAMA. I’m using google colab, I already cloned the repository and installed the required packages.
They said you can use any model from the hugging face transformers but I can’t figure out where to get the “model” and “model_args” parameters:
# running 3-shot with CoT for GPT-4V on ENEM 2022
python main.py \
--model chatgpt \
--model_args engine=gpt-4-vision-preview \
--tasks enem_cot_2022_blind,enem_cot_2022_images,enem_cot_2022_captions \
--description_dict_path description.json \
--num_fewshot 3 \
--conversation_template chatgpt
If you go to the Llama model in hugging face and click in “Use in Transformers” you get this:
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B")
model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B")
So I tried using “model = meta-llama” and “model_args = Meta-Llama-3-8B” but that doesn’t work.
Like so:
!python main.py \
--model meta-llama \
--model_args Meta-Llama-3-8B \
--tasks enem_cot_2022_blind,enem_cot_2022_captions \
--description_dict_path description.json \
--num_fewshot 3
I get:
Selected Tasks: ['enem_cot_2022_blind', 'enem_cot_2022_captions']
Traceback (most recent call last):
File "/content/gpt-4-enem/main.py", line 112, in <module>
main()
File "/content/gpt-4-enem/main.py", line 81, in main
results = evaluator.simple_evaluate(
File "/content/gpt-4-enem/lm_eval/utils.py", line 164, in _wrapper
return fn(*args, **kwargs)
File "/content/gpt-4-enem/lm_eval/evaluator.py", line 66, in simple_evaluate
lm = lm_eval.models.get_model(model).create_from_arg_string(
File "/content/gpt-4-enem/lm_eval/models/__init__.py", line 16, in get_model
return MODEL_REGISTRY[model_name]
KeyError: 'meta-llama'