Merge branch 'main' into nightly

pyproject.toml

@@ -60,6 +60,9 @@ windows=[
     "bitsandbytes>=0.45.5 ; platform_system == 'Windows'",
     "xformers>=0.0.22.post7 ; platform_system == 'Windows'",
 ]
+base = [
+    "unsloth[huggingface]",
+]
 cu118only = [
     "xformers @ https://download.pytorch.org/whl/cu118/xformers-0.0.22.post7%2Bcu118-cp39-cp39-manylinux2014_x86_64.whl ; python_version=='3.9' and platform_system == 'Linux'",
     "xformers @ https://download.pytorch.org/whl/cu118/xformers-0.0.22.post7%2Bcu118-cp310-cp310-manylinux2014_x86_64.whl ; python_version=='3.10' and platform_system == 'Linux'",

unsloth/models/_utils.py

@@ -76,6 +76,7 @@ platform_system = platform_system()
 import numpy as np
 import contextlib
 import re
+import functools
 import warnings, subprocess, re, inspect, psutil, os, math
 from unsloth_zoo.utils import Version
 from unsloth import DEVICE_TYPE, DEVICE_COUNT
@@ -422,6 +423,7 @@ HAS_FLASH_ATTENTION_SOFTCAPPING = False
 
 if DEVICE_TYPE == "cuda":
     major_version, minor_version = torch.cuda.get_device_capability()
+    torch.cuda.get_device_capability = functools.cache(torch.cuda.get_device_capability)
 
     if major_version >= 8:
         SUPPORTS_BFLOAT16 = True
@@ -586,7 +588,6 @@ UNSLOTH_COMPILE_DEBUG         = os.environ.get("UNSLOTH_COMPILE_DEBUG",
 UNSLOTH_COMPILE_MAXIMUM       = os.environ.get("UNSLOTH_COMPILE_MAXIMUM",       "0") == "1"
 UNSLOTH_COMPILE_IGNORE_ERRORS = os.environ.get("UNSLOTH_COMPILE_IGNORE_ERRORS", "1") == "1"
 # Just remove max_autotune_gemm warning
-import functools
 from torch._inductor.runtime.hints import DeviceProperties
 
 @functools.lru_cache(None)

unsloth/models/loader.py

@@ -592,6 +592,14 @@ class FastModel(FastBaseModel):
                 "os.environ['TRITON_F32_DEFAULT'] = 'ieee';"
         elif "gpt-oss" in lowered_model_name:
             os.environ["UNSLOTH_DISABLE_STATIC_GENERATION"] = "1"
+            if not load_in_4bit:
+                # Only upcast MoE biases for MXFP4, not BnB
+                os.environ["UNSLOTH_FORCE_CUSTOM_DTYPE"] = \
+                    "all;None;None;"\
+                    "x = 'gate_up_proj_bias'\n"\
+                    "if hasattr(module, x): setattr(module, x, torch.nn.Parameter(getattr(module, x).to(torch.float32)) if isinstance(getattr(module, x), torch.nn.Parameter) else getattr(module, x).to(torch.float32))\n"\
+                    "x = 'down_proj_bias'\n"\
+                    "if hasattr(module, x): setattr(module, x, torch.nn.Parameter(getattr(module, x).to(torch.float32)) if isinstance(getattr(module, x), torch.nn.Parameter) else getattr(module, x).to(torch.float32))\n;"
         else:
             for check_model_name in DISABLE_COMPILE_MODEL_NAMES:
                 if check_model_name in lowered_model_name:

unsloth/models/mapper.py

@@ -924,12 +924,12 @@ __INT_TO_FLOAT_MAPPER = \
     "unsloth/gpt-oss-20b-unsloth-bnb-4bit" : (
         "unsloth/gpt-oss-20b",
         "openai/gpt-oss-20b",
-        "unsloth/gpt-oss-20b-bnb-4bit",
+        "unsloth/gpt-oss-20b-unsloth-bnb-4bit",
     ),
     "unsloth/gpt-oss-120b-unsloth-bnb-4bit" : (
         "unsloth/gpt-oss-120b",
         "openai/gpt-oss-120b",
-        "unsloth/gpt-oss-120b-bnb-4bit",
+        "unsloth/gpt-oss-120b-unsloth-bnb-4bit",
     ),
 }
 

unsloth/models/vision.py

@@ -365,8 +365,10 @@ class FastBaseModel:
             allow_float16_runs = (checker == "float16" and dtype == torch.float16)
 
             if allow_all_runs or allow_float16_runs:
-                dtype = eval(_dtype)
-                bnb_compute_dtype = eval(_bnb_compute_dtype)
+                if eval(_dtype) is not None:
+                    dtype = eval(_dtype)
+                if eval(_bnb_compute_dtype) is not None:
+                    bnb_compute_dtype = eval(_bnb_compute_dtype)
                 correct_dtype = bnb_compute_dtype
                 custom_datatype = _custom_datatype
                 # Execute code as well
@@ -421,6 +423,10 @@ class FastBaseModel:
             os.environ["UNSLOTH_ENABLE_FULL_FINETUNING"] = "0"
         pass
 
+        # Fix AttributeError: 'BitsAndBytesConfig' object has no attribute 'get_loading_attributes'
+        if bnb_config is not None and not hasattr(bnb_config, "get_loading_attributes"):
+            bnb_config.get_loading_attributes = lambda *args, **kwargs: {}
+
         # Cannot be None, since HF now checks for the config
         if load_in_4bit: kwargs["quantization_config"] = bnb_config
 
@@ -429,23 +435,16 @@ class FastBaseModel:
         if do_forced_float32: torch_dtype = torch.bfloat16
 
         raise_handler = RaiseUninitialized()
-        # MXFP4 -> BF16 GPT-OSS check
-        if "gpt-oss" in os.environ.get("UNSLOTH_MODEL_NAME", "") and \
-            "quantization_config" not in kwargs:
-
-            from unsloth_zoo.temporary_patches.gpt_oss import load_gpt_oss_MXFP4
-            model = load_gpt_oss_MXFP4(model_name, torch_dtype)
-        else:
-            model = auto_model.from_pretrained(
-                model_name,
-                device_map              = device_map,
-                torch_dtype             = torch_dtype,
-                # quantization_config   = bnb_config,
-                token                   = token,
-                trust_remote_code       = trust_remote_code,
-                # attn_implementation   = attn_implementation,
-                **kwargs,
-            )
+        model = auto_model.from_pretrained(
+            model_name,
+            device_map              = device_map,
+            torch_dtype             = torch_dtype,
+            # quantization_config   = bnb_config,
+            token                   = token,
+            trust_remote_code       = trust_remote_code,
+            # attn_implementation   = attn_implementation,
+            **kwargs,
+        )
         raise_handler.remove()
         # Return old flag
         os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = old_hf_transfer