[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
This commit is contained in:
pre-commit-ci[bot] 2026-01-02 13:58:49 +00:00
commit f23735af0a
2 changed files with 10 additions and 4 deletions

View file

@ -101,7 +101,9 @@ if os.environ.get("UNSLOTH_ENABLE_LOGGING", "0") != "1":
# Skipping import of cpp extensions due to incompatible torch version 2.9.0+cu128 for torchao version 0.15.0
logging.getLogger("torchao").setLevel(logging.ERROR)
# SyntaxWarning: invalid escape sequence '\.'
warnings.filterwarnings("ignore", message = "invalid escape sequence", category = SyntaxWarning)
warnings.filterwarnings(
"ignore", message = "invalid escape sequence", category = SyntaxWarning
)
# Fix up AttributeError: 'MessageFactory' object has no attribute 'GetPrototype'
@ -549,5 +551,8 @@ def fix_diffusers_warnings():
def fix_huggingface_hub():
# huggingface_hub.is_offline_mode got removed, so add it back
import huggingface_hub
if not hasattr(huggingface_hub, "is_offline_mode"):
huggingface_hub.is_offline_mode = lambda: huggingface_hub.constants.HF_HUB_OFFLINE
huggingface_hub.is_offline_mode = (
lambda: huggingface_hub.constants.HF_HUB_OFFLINE
)

View file

@ -2386,6 +2386,7 @@ def make_fast_generate_wrapper(original_generate):
Creates a wrapper around model.generate that checks for incorrect
vLLM-style usage when fast_inference=False.
"""
@functools.wraps(original_generate)
def _fast_generate_wrapper(*args, **kwargs):
# Check for vLLM-specific arguments
@ -2419,9 +2420,9 @@ def make_fast_generate_wrapper(original_generate):
"when `fast_inference=True` (vLLM). Since `fast_inference=False`, you must "
"tokenize the input first:\n\n"
" messages = tokenizer.apply_chat_template(\n"
" [{\"role\": \"user\", \"content\": \"Your prompt here\"}],\n"
' [{"role": "user", "content": "Your prompt here"}],\n'
" tokenize=True, add_generation_prompt=True,\n"
" return_tensors=\"pt\", return_dict=True\n"
' return_tensors="pt", return_dict=True\n'
" )\n"
" output = model.fast_generate(\n"
" **messages.to('cuda'),\n"