split up llama model loading so config can be loaded from base config and models can be loaded from a path

src/axolotl/utils/models.py

@@ -10,7 +10,7 @@ from typing import TYPE_CHECKING, Optional, Tuple  # noqa: F401
 import bitsandbytes as bnb
 import torch
 import transformers
-from transformers import AutoModelForCausalLM  # noqa: F401
+from transformers import AutoModelForCausalLM, LlamaConfig  # noqa: F401
 from transformers import PreTrainedModel  # noqa: F401
 from transformers import AutoConfig, AutoTokenizer, BitsAndBytesConfig
 
@@ -172,8 +172,10 @@ def load_model(
             )
             load_in_8bit = False
         elif is_llama_derived_model and "LlamaForCausalLM" in globals():
+            config = LlamaConfig.from_pretrained(base_model_config)
             model = LlamaForCausalLM.from_pretrained(
                 base_model,
+                config=config,
                 load_in_8bit=cfg.load_in_8bit and cfg.adapter is not None,
                 load_in_4bit=cfg.load_in_4bit and cfg.adapter is not None,
                 torch_dtype=torch_dtype,