add float16 docs and tweak typehints

README.md

@@ -264,6 +264,8 @@ See sample configs in [configs](configs) folder or [examples](examples) for quic
   bf16: true # require >=ampere
   fp16: true
   tf32: true # require >=ampere
+  bfloat16: true # require >=ampere, use instead of bf16 when you don't want AMP
+  float16: true # use instead of fp16 when you don't want AMP
   ```
   Note: Repo does not do 4-bit quantization.
 
@@ -522,6 +524,12 @@ Add below flag to train command above
 --merge_lora --lora_model_dir="./completed-model" --load_in_8bit=False --load_in_4bit=False
 ```
 
+If you run out of CUDA memory, you can try to merge in system RAM with
+
+```bash
+CUDA_VISIBLE_DEVICES="" python3 scripts/finetune.py ...
+```
+
 ## Common Errors 🧰
 
 > Cuda out of memory

src/axolotl/utils/models.py

@@ -11,13 +11,14 @@ import bitsandbytes as bnb
 import torch
 import transformers
 from optimum.bettertransformer import BetterTransformer
-from transformers import PreTrainedModel  # noqa: F401
+from transformers import (  # noqa: F401
-from transformers import (
     AutoConfig,
     AutoModelForCausalLM,
     AutoTokenizer,
     BitsAndBytesConfig,
     LlamaConfig,
+    PreTrainedModel,
+    PreTrainedTokenizerBase,
 )
 
 from axolotl.prompt_tokenizers import LLAMA_DEFAULT_PAD_TOKEN
@@ -71,7 +72,7 @@ def load_tokenizer(
 def load_model(
     base_model, base_model_config, model_type, tokenizer, cfg, adapter="lora"
 ):
-    # type: (str, str, str, AutoTokenizer, DictDefault, Optional[str]) -> Tuple[PreTrainedModel, Optional[PeftConfig]]
+    # type: (str, str, str, PreTrainedTokenizerBase, DictDefault, Optional[str]) -> Tuple[PreTrainedModel, Optional[PeftConfig]]
     """
     Load a model from a base model and a model type.
     """
@@ -284,6 +285,7 @@ def load_model(
         model = AutoModelForCausalLM.from_pretrained(
             base_model,
             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,
             device_map=cfg.device_map,
             trust_remote_code=cfg.trust_remote_code or False,