Nightly

pyproject.toml

@@ -60,7 +60,7 @@ huggingfacenotorch = [
 ]
 huggingface = [
     "unsloth[huggingfacenotorch]",
-    "unsloth_zoo>=2025.12.3",
+    "unsloth_zoo>=2025.12.4",
     "torchvision",
     "unsloth[triton]",
 ]
@@ -523,7 +523,7 @@ colab-ampere-torch220 = [
     "flash-attn>=2.6.3 ; ('linux' in sys_platform)",
 ]
 colab-new = [
-    "unsloth_zoo>=2025.12.3",
+    "unsloth_zoo>=2025.12.4",
     "packaging",
     "tyro",
     "transformers>=4.51.3,!=4.52.0,!=4.52.1,!=4.52.2,!=4.52.3,!=4.53.0,!=4.54.0,!=4.55.0,!=4.55.1,!=4.57.0,<=4.57.3",

unsloth/__init__.py

@@ -17,6 +17,13 @@
 import os, re, subprocess, inspect, functools
 import numpy as np
 
+# Log Unsloth is being used
+os.environ["UNSLOTH_IS_PRESENT"] = "1"
+
+# Check if modules that need patching are already imported
+critical_modules = ["trl", "transformers", "peft"]
+already_imported = [mod for mod in critical_modules if mod in sys.modules]
+
 # Fix some issues before importing other packages
 from .import_fixes import (
     fix_message_factory_issue,
@@ -31,10 +38,6 @@
 del check_fbgemm_gpu_version
 del torchvision_compatibility_check
 
-# Check if modules that need patching are already imported
-critical_modules = ["trl", "transformers", "peft"]
-already_imported = [mod for mod in critical_modules if mod in sys.modules]
-
 # This check is critical because Unsloth optimizes these libraries by modifying
 # their code at import time. If they're imported first, the original (slower,
 # more memory-intensive) implementations will be used instead of Unsloth's
@@ -43,7 +46,7 @@
     # stacklevel=2 makes warning point to user's import line rather than this library code,
     # showing them exactly where to fix the import order in their script
     warnings.warn(
-        f"WARNING: Unsloth should be imported before {', '.join(already_imported)} "
+        f"WARNING: Unsloth should be imported before [{', '.join(already_imported)}] "
         f"to ensure all optimizations are applied. Your code may run slower or encounter "
         f"memory issues without these optimizations.\n\n"
         f"Please restructure your imports with 'import unsloth' at the top of your file.",
@@ -63,16 +66,14 @@
 #    "pinned_use_cuda_host_register:True,"\
 #    "pinned_num_register_threads:8"
 
-# Log Unsloth is being used
-os.environ["UNSLOTH_IS_PRESENT"] = "1"
 
 from importlib.metadata import version as importlib_version
 from importlib.metadata import PackageNotFoundError
 
 # Check for unsloth_zoo
 try:
     unsloth_zoo_version = importlib_version("unsloth_zoo")
-    if Version(unsloth_zoo_version) < Version("2025.12.3"):
+    if Version(unsloth_zoo_version) < Version("2025.12.4"):
         print(
             "Unsloth: Please update Unsloth and Unsloth-Zoo to the latest version!\n"
             "Do this via `pip install --upgrade --force-reinstall --no-cache-dir --no-deps unsloth unsloth_zoo`"
@@ -123,6 +124,8 @@
     patch_ipykernel_hf_xet,
     patch_trackio,
     patch_datasets,
+    patch_enable_input_require_grads,
+    fix_openenv_no_vllm,
 )
 
 fix_xformers_performance_issue()
@@ -132,6 +135,8 @@
 patch_ipykernel_hf_xet()
 patch_trackio()
 patch_datasets()
+patch_enable_input_require_grads()
+fix_openenv_no_vllm()
 
 del fix_xformers_performance_issue
 del fix_vllm_aimv2_issue
@@ -140,6 +145,8 @@
 del patch_ipykernel_hf_xet
 del patch_trackio
 del patch_datasets
+del patch_enable_input_require_grads
+del fix_openenv_no_vllm
 
 # Torch 2.4 has including_emulation
 if DEVICE_TYPE == "cuda":

unsloth/import_fixes.py

@@ -19,8 +19,8 @@
 from packaging.version import Version as TrueVersion
 import re
 import logging
-
-UNSLOTH_ENABLE_LOGGING = os.environ.get("UNSLOTH_ENABLE_LOGGING", "0") == "1"
+# Cannot import logger here since it'll import transformers
+# from unsloth_zoo.log import logger
 
 
 def Version(version):
@@ -70,9 +70,10 @@ def GetMessages(self, *args, **kwargs):
             def GetPrototype(self, *args, **kwargs):
                 return
 
+        from unsloth_zoo.log import logger
+
         if not hasattr(google.protobuf.message_factory, "MessageFactory"):
-            if UNSLOTH_ENABLE_LOGGING:
-                print("Unsloth: Patching protobuf.MessageFactory as it doesn't exist")
+            logger.info("Unsloth: Patching protobuf.MessageFactory as it doesn't exist")
             google.protobuf.message_factory.MessageFactory = MessageFactory
         elif (
             hasattr(google.protobuf.message_factory, "MessageFactory")
@@ -82,8 +83,7 @@ def GetPrototype(self, *args, **kwargs):
             and not hasattr(google.protobuf.message_factory, "GetMessageClass")
         ):
             google.protobuf.message_factory.MessageFactory = MessageFactory
-            if UNSLOTH_ENABLE_LOGGING:
-                print("Unsloth: Patching protobuf.MessageFactory as it doesn't exist")
+            logger.info("Unsloth: Patching protobuf.MessageFactory as it doesn't exist")
         elif (
             hasattr(google.protobuf.message_factory, "MessageFactory")
             and not hasattr(
@@ -97,8 +97,7 @@ def GetPrototype(self, descriptor):
                 return GetMessageClass(descriptor)
 
             google.protobuf.message_factory.MessageFactory.GetPrototype = GetPrototype
-            if UNSLOTH_ENABLE_LOGGING:
-                print("Unsloth: Patching protobuf.MessageFactory.GetPrototype")
+            logger.info("Unsloth: Patching protobuf.MessageFactory.GetPrototype")
         pass
     except:
         pass
@@ -110,6 +109,8 @@ def fix_xformers_performance_issue():
         return
     xformers_version = importlib_version("xformers")
     if Version(xformers_version) < Version("0.0.29"):
+        from unsloth_zoo.log import logger
+
         xformers_location = importlib.util.find_spec("xformers").origin
         xformers_location = os.path.split(xformers_location)[0]
         cutlass = Path(xformers_location) / "ops" / "fmha" / "cutlass.py"
@@ -126,13 +127,11 @@ def fix_xformers_performance_issue():
                         f.seek(0)
                         f.write(text)
                         f.truncate()
-                        if UNSLOTH_ENABLE_LOGGING:
-                            print(
-                                "Unsloth: Patching Xformers to fix some performance issues."
-                            )
+                        logger.info(
+                            "Unsloth: Patching Xformers to fix some performance issues."
+                        )
         except Exception as e:
-            if UNSLOTH_ENABLE_LOGGING:
-                print(f"Unsloth: Failed patching Xformers with error = {str(e)}")
+            logger.info(f"Unsloth: Failed patching Xformers with error = {str(e)}")
 
 
 # ValueError: 'aimv2' is already used by a Transformers config, pick another name.
@@ -141,6 +140,8 @@ def fix_vllm_aimv2_issue():
         return
     vllm_version = importlib_version("vllm")
     if Version(vllm_version) < Version("0.10.1"):
+        from unsloth_zoo.log import logger
+
         vllm_version = importlib.util.find_spec("vllm").origin
         vllm_version = os.path.split(vllm_version)[0]
         ovis_config = Path(vllm_version) / "transformers_utils" / "configs" / "ovis.py"
@@ -167,13 +168,11 @@ def fix_vllm_aimv2_issue():
                         f.seek(0)
                         f.write(text)
                         f.truncate()
-                        if UNSLOTH_ENABLE_LOGGING:
-                            print(
-                                "Unsloth: Patching vLLM to fix `'aimv2' is already used by a Transformers config, pick another name.`"
-                            )
+                        logger.info(
+                            "Unsloth: Patching vLLM to fix `'aimv2' is already used by a Transformers config, pick another name.`"
+                        )
         except Exception as e:
-            if UNSLOTH_ENABLE_LOGGING:
-                print(f"Unsloth: Failed patching vLLM with error = {str(e)}")
+            logger.info(f"Unsloth: Failed patching vLLM with error = {str(e)}")
 
 
 def fix_vllm_guided_decoding_params():
@@ -274,8 +273,74 @@ def check_fbgemm_gpu_version():
         raise ImportError(
             f"Unsloth: fbgemm_gpu_genai=={fbgemm_gpu_version} detected. It might cause unexpected issues like segmentation faults. Please uninstall the current one by doing `pip uninstall fbgemm-gpu` && `pip install fbgemm-gpu` to install fbgemm-gpu 1.4.0 or newer!"
         )
-    elif UNSLOTH_ENABLE_LOGGING:
-        print(f"Unsloth: fbgemm_gpu_genai=={fbgemm_gpu_version} detected.")
+    from unsloth_zoo.log import logger
+
+    logger.info(f"Unsloth: fbgemm_gpu_genai=={fbgemm_gpu_version} detected.")
+
+
+def patch_enable_input_require_grads():
+    """
+    Patch transformers PreTrainedModel.enable_input_require_grads to handle vision models
+    that raise NotImplementedError from get_input_embeddings().
+
+    """
+    import inspect
+    from transformers import PreTrainedModel
+
+    # Check if the original function iterates over self.modules() instead of just returning the enable_input_require_grads
+    # Ref: https://github.com/huggingface/transformers/pull/41993/files#diff-6b72b98c4c2dcfc6cc606843917733f5d858374fbc22a735ff483bbc0c1e63eaL1979-R1996
+    try:
+        original_source = inspect.getsource(PreTrainedModel.enable_input_require_grads)
+    except:
+        return
+
+    # Only patch if the new pattern exists (iterating over self.modules())
+    if "for module in self.modules()" not in original_source:
+        return
+
+    def _patched_enable_input_require_grads(self):
+        def make_inputs_require_grads(module, input, output):
+            output.requires_grad_(True)
+
+        hooks = []
+        seen_modules = set()
+
+        for module in self.modules():
+            if not (
+                isinstance(module, PreTrainedModel)
+                and hasattr(module, "get_input_embeddings")
+            ):
+                continue
+
+            try:
+                input_embeddings = module.get_input_embeddings()
+            except NotImplementedError:
+                # Vision models may not implement get_input_embeddings - skip them
+                # For GLM V4.6 for example, this skips only `self.visual`
+                continue
+
+            if input_embeddings is None:
+                continue
+
+            embedding_id = id(input_embeddings)
+            if embedding_id in seen_modules:
+                continue
+
+            seen_modules.add(embedding_id)
+            hooks.append(
+                input_embeddings.register_forward_hook(make_inputs_require_grads)
+            )
+
+        self._require_grads_hooks = hooks
+        if hooks:
+            self._require_grads_hook = hooks[0]
+
+    PreTrainedModel.enable_input_require_grads = _patched_enable_input_require_grads
+    from unsloth_zoo.log import logger
+
+    logger.info(
+        "Unsloth: Patched enable_input_require_grads for vision model compatibility"
+    )
 
 
 def torchvision_compatibility_check():
@@ -313,7 +378,49 @@ def torchvision_compatibility_check():
             f"but found torchvision=={torchvision_version}. "
             f"Please refer to https://pytorch.org/get-started/previous-versions/ for more information."
         )
-    elif UNSLOTH_ENABLE_LOGGING:
-        print(
-            f"Unsloth: torch=={torch_version} and torchvision=={torchvision_version} are compatible."
-        )
+    from unsloth_zoo.log import logger
+
+    logger.info(
+        f"Unsloth: torch=={torch_version} and torchvision=={torchvision_version} are compatible."
+    )
+
+
+# Fix TRL OpenEnv 0.26 NameError: name 'SamplingParams' is not defined
+def fix_openenv_no_vllm():
+    if importlib.util.find_spec("trl") is None:
+        return
+    trl_location = importlib.util.find_spec("trl").origin
+    trl_location = os.path.split(trl_location)[0]
+    openenv = Path(trl_location) / "experimental" / "openenv" / "utils.py"
+    if not openenv.exists():
+        return
+    from unsloth_zoo.log import logger
+
+    try:
+        with open(openenv, "r+", encoding = "utf-8") as f:
+            text = f.read()
+            bad = (
+                "if is_vllm_available():\n"
+                "    from vllm import SamplingParams\n"
+                "    from vllm.sampling_params import GuidedDecodingParams\n"
+            )
+            if bad + "\n" + "\n" in text:
+                text = text.replace(
+                    bad + "\n" + "\n",
+                    bad
+                    + (
+                        "else:\n"
+                        "    from typing import Any\n"
+                        "    SamplingParams = Any\n"
+                        "    GuidedDecodingParams = Any\n"
+                        "\n"
+                    ),
+                )
+                f.seek(0)
+                f.write(text)
+                f.truncate()
+                logger.info(
+                    "Unsloth: Patching TRL OpenEnv to fix SamplingParams not defined"
+                )
+    except Exception as e:
+        logger.info(f"Unsloth: Failed patching TRL OpenEnv with error = {str(e)}")

unsloth/kernels/rope_embedding.py

@@ -20,13 +20,6 @@
 from .utils import calculate_settings, torch_gpu_device, torch_device_stream
 
 
-@triton.heuristics(
-    {
-        "BACKWARD_PASS": lambda args: bool(args["BACKWARD_PASS"]),
-        "HAS_ROPE_INDICES": lambda args: bool(args["HAS_ROPE_INDICES"]),
-    }
-)
-@triton.jit
 def _rope_embedding_QK(
     Q,
     Q_batch_stride,
@@ -104,6 +97,15 @@ def _rope_embedding_QK(
         tl.store(k_ptr + half_head_dim + col_offsets, k1 * cos1 + k0 * sin1, mask = mask)
 
 
+_rope_embedding_QK = triton.jit(_rope_embedding_QK)
+_rope_embedding_QK = triton.heuristics(
+    {
+        "BACKWARD_PASS": lambda args: bool(args["BACKWARD_PASS"]),
+        "HAS_ROPE_INDICES": lambda args: bool(args["HAS_ROPE_INDICES"]),
+    }
+)(_rope_embedding_QK)
+
+
 ROPE_GROUP_SIZE: int = 4
 
 

unsloth/models/_utils.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "2025.12.4"
+__version__ = "2025.12.5"
 
 __all__ = [
     "SUPPORTS_BFLOAT16",
@@ -413,6 +413,16 @@ def filter(self, x):
 except:
     pass
 
+# Flax classes are deprecated and will be removed in Diffusers v1.0.0.
+try:
+    from diffusers.utils import logger as diffusers_logger
+
+    diffusers_logger.addFilter(HideLoggingMessage("are deprecated"))
+    del diffusers_logger
+except:
+    pass
+
+
 # Errors out on
 # Some weights of Gemma3nForConditionalGeneration were not initialized from the model checkpoint
 from transformers.modeling_utils import logger as transformers_logger