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use exact model name

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This commit is contained in:
Itsuro Tajima 2024-11-26 20:20:34 +09:00
commit 4cae1aa0be
1 changed files with 20 additions and 6 deletions
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26
unsloth/models/loader.py
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@ -78,12 +78,14 @@ class FastLanguageModel(FastLlamaModel):
use_gradient_checkpointing = "unsloth",
resize_model_vocab = None,
revision = None,
use_exact_model_name = False,
*args, **kwargs,
):
if token is None: token = get_token()
old_model_name = model_name
model_name = get_model_name(model_name, load_in_4bit)
if not use_exact_model_name:
model_name = get_model_name(model_name, load_in_4bit)
# First check if it's a normal model via AutoConfig
from huggingface_hub.utils import disable_progress_bars, enable_progress_bars, are_progress_bars_disabled
@ -162,7 +164,10 @@ class FastLanguageModel(FastLlamaModel):
# Get base model for PEFT:
if is_peft:
# Check base model again for PEFT
model_name = get_model_name(peft_config.base_model_name_or_path, load_in_4bit)
if not use_exact_model_name:
model_name = get_model_name(peft_config.base_model_name_or_path, load_in_4bit)
else:
model_name = peft_config.base_model_name_or_path
model_config = AutoConfig.from_pretrained(
model_name,
token = token,
@ -249,6 +254,8 @@ class FastLanguageModel(FastLlamaModel):
tokenizer_name = None
pass
original_kwargs = kwargs.copy()
model, tokenizer = dispatch_model.from_pretrained(
model_name = model_name,
max_seq_length = max_seq_length,
@ -262,7 +269,7 @@ class FastLanguageModel(FastLlamaModel):
tokenizer_name = tokenizer_name,
trust_remote_code = trust_remote_code,
revision = revision if not is_peft else None,
*args, **kwargs,
*args, **original_kwargs,
)
if resize_model_vocab is not None:
@ -347,6 +354,7 @@ class FastVisionModel(FastBaseVisionModel):
use_gradient_checkpointing = "unsloth",
resize_model_vocab = None, # [TODO] No effect
revision = None,
use_exact_model_name = False,
*args, **kwargs,
):
if token is None: token = get_token()
@ -357,7 +365,8 @@ class FastVisionModel(FastBaseVisionModel):
patch_unsloth_smart_gradient_checkpointing()
old_model_name = model_name
model_name = get_model_name(model_name, load_in_4bit)
if not use_exact_model_name:
model_name = get_model_name(model_name, load_in_4bit)
with contextlib.redirect_stdout(open(os.devnull, "w")):
patch_loss_functions(torch_compile = False)
@ -462,7 +471,10 @@ class FastVisionModel(FastBaseVisionModel):
# Get base model for PEFT:
if is_peft:
# Check base model again for PEFT
model_name = get_model_name(peft_config.base_model_name_or_path, load_in_4bit)
if not use_exact_model_name:
model_name = get_model_name(peft_config.base_model_name_or_path, load_in_4bit)
else:
model_name = peft_config.base_model_name_or_path
model_config = AutoConfig.from_pretrained(
model_name,
token = token,
@ -483,6 +495,8 @@ class FastVisionModel(FastBaseVisionModel):
tokenizer_name = None
pass
original_kwargs = kwargs.copy()
model, tokenizer = FastBaseVisionModel.from_pretrained(
model_name = model_name,
max_seq_length = max_seq_length,
@ -494,7 +508,7 @@ class FastVisionModel(FastBaseVisionModel):
revision = revision if not is_peft else None,
model_types = model_types,
tokenizer_name = tokenizer_name,
*args, **kwargs,
*args, **original_kwargs,
)
if resize_model_vocab is not None: