Fix transformers 4.57.1

pyproject.toml

@@ -39,11 +39,10 @@ triton = [
     "triton>=3.0.0 ; ('linux' in sys_platform)",
     "triton-windows ; (sys_platform == 'win32') and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
 ]
-huggingface = [
-    "unsloth_zoo>=2025.10.4",
+huggingfacenotorch = [
+    "unsloth_zoo>=2025.10.5",
     "wheel>=0.42.0",
     "packaging",
-    "torchvision",
     "numpy",
     "tqdm",
     "psutil",
@@ -58,6 +57,10 @@ huggingface = [
     "diffusers",
     "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,<=4.56.2",
     "trl>=0.7.9,!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,!=0.15.0,!=0.19.0,<=0.23.0",
+]
+huggingface = [
+    "unsloth[huggingfacenotorch]",
+    "torchvision",
     "unsloth[triton]",
 ]
 windows = [
@@ -458,7 +461,7 @@ colab-ampere-torch220 = [
     "flash-attn>=2.6.3 ; ('linux' in sys_platform)",
 ]
 colab-new = [
-    "unsloth_zoo>=2025.10.4",
+    "unsloth_zoo>=2025.10.5",
     "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,<=4.56.2",
@@ -740,7 +743,12 @@ intel-gpu-torch270 = [
     "torch @ https://download.pytorch.org/whl/xpu/torch-2.7.0%2Bxpu-cp312-cp312-linux_x86_64.whl#sha256=c806d44aa2ca5d225629f6fbc6c994d5deaac2d2cde449195bc8e3522ddd219a ; ('linux' in sys_platform) and python_version == '3.12' and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
     "torch @ https://download.pytorch.org/whl/xpu/torch-2.7.0%2Bxpu-cp313-cp313-linux_x86_64.whl#sha256=25d8277b7f01d42e2e014ccbab57a2692b6ec4eff8dcf894eda1b297407cf97a ; ('linux' in sys_platform) and python_version == '3.13' and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
 ]
-
+amd = [
+    "unsloth[huggingfacenotorch]",
+    "bitsandbytes @ https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-manylinux_2_24_x86_64.whl ; ('linux' in sys_platform) and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
+    "bitsandbytes @ https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-win_amd64.whl ; (sys_platform == 'win32') and (platform_machine == 'AMD64' or platform_machine == 'x86_64')",
+    "bitsandbytes @ https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-manylinux_2_24_aarch64.whl ; ('linux' in sys_platform) and (platform_machine == 'aarch64')",
+]
 [project.urls]
 homepage = "http://www.unsloth.ai"
 documentation = "https://github.com/unslothai/unsloth"

unsloth/__init__.py

@@ -69,49 +69,14 @@
     raise exception
 pass
 
-@functools.cache
-def is_hip():
-    return bool(getattr(getattr(torch, "version", None), "hip", None))
-pass
-
-@functools.cache
-def get_device_type():
-    if hasattr(torch, "cuda") and torch.cuda.is_available():
-        if is_hip():
-            return "hip"
-        return "cuda"
-    elif hasattr(torch, "xpu") and torch.xpu.is_available():
-        return "xpu"
-    # Check torch.accelerator
-    if hasattr(torch, "accelerator"):
-        if not torch.accelerator.is_available():
-            raise NotImplementedError("Unsloth cannot find any torch accelerator? You need a GPU.")
-        accelerator = str(torch.accelerator.current_accelerator())
-        if accelerator in ("cuda", "xpu", "hip"):
-            raise RuntimeError(
-                f"Unsloth: Weirdly `torch.cuda.is_available()`, `torch.xpu.is_available()` and `is_hip` all failed.\n"\
-                f"But `torch.accelerator.current_accelerator()` works with it being = `{accelerator}`\n"\
-                f"Please reinstall torch - it's most likely broken :("
-            )
-    raise NotImplementedError("Unsloth currently only works on NVIDIA, AMD and Intel GPUs.")
-pass
-DEVICE_TYPE : str = get_device_type()
-# HIP fails for autocast and other torch functions. Use CUDA instead
-DEVICE_TYPE_TORCH = DEVICE_TYPE
-if DEVICE_TYPE_TORCH == "hip": DEVICE_TYPE_TORCH = "cuda"
-
-@functools.cache
-def get_device_count():
-    if DEVICE_TYPE in ("cuda", "hip"):
-        return torch.cuda.device_count()
-    elif DEVICE_TYPE == "xpu":
-        return torch.xpu.device_count()
-    else:
-        return 1
-pass
-
-DEVICE_COUNT : int = get_device_count()
-
+from .device_type import (
+    is_hip,
+    get_device_type,
+    DEVICE_TYPE,
+    DEVICE_TYPE_TORCH,
+    DEVICE_COUNT,
+    ALLOW_PREQUANTIZED_MODELS,
+)
 # Reduce VRAM usage by reducing fragmentation
 # And optimize pinning of memory
 # TODO(billishyahao): need to add hip related optimization...
@@ -201,7 +166,10 @@ def is_bf16_supported(): return SUPPORTS_BFLOAT16
     else: from triton.common.build import libcuda_dirs
 
     # Try loading bitsandbytes and triton
-    import bitsandbytes as bnb
+    try:
+        import bitsandbytes as bnb
+    except:
+        print("Unsloth: `bitsandbytes` is not installed - 4bit QLoRA unallowed, but 16bit and full finetuning works!")
     try:
         cdequantize_blockwise_fp32 = bnb.functional.lib.cdequantize_blockwise_fp32
         libcuda_dirs()

unsloth/_amd_install.sh

@@ -0,0 +1,32 @@
+#!/usr/bin/env bash
+# _amd_install.sh
+# Non-interactive installer: build tools, PyTorch (ROCm 6.4), bitsandbytes (HIP), and Unsloth from source.
+# Usage:
+#   bash _amd_install.sh
+#
+
+set -euo pipefail
+export DEBIAN_FRONTEND=noninteractive
+
+apt-get update
+apt-get install -y --no-install-recommends build-essential cmake git
+
+pip install \
+    torch==2.8.0 torchvision torchaudio torchao==0.13.0 xformers \
+    --index-url https://download.pytorch.org/whl/rocm6.4
+
+WORKDIR="$(pwd)"
+TMPDIR="$(mktemp -d)"
+cd "$TMPDIR"
+git clone https://github.com/bitsandbytes-foundation/bitsandbytes.git
+cd bitsandbytes
+arch
+cmake -DCOMPUTE_BACKEND=hip -S .
+make -j"$(nproc)"
+pip install .
+cd "$WORKDIR"
+rm -rf "$TMPDIR"
+
+pip install --no-deps unsloth unsloth-zoo
+pip install "unsloth_zoo[base] @ git+https://github.com/unslothai/unsloth-zoo"
+pip install "unsloth[base] @ git+https://github.com/unslothai/unsloth"

unsloth/device_type.py

@@ -0,0 +1,80 @@
+# Copyright 2023-present Daniel Han-Chen & the Unsloth team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+__all__ = [
+    "is_hip",
+    "get_device_type",
+    "DEVICE_TYPE",
+    "DEVICE_TYPE_TORCH",
+    "DEVICE_COUNT",
+    "ALLOW_PREQUANTIZED_MODELS",
+]
+
+import torch
+import functools
+
+@functools.cache
+def is_hip():
+    return bool(getattr(getattr(torch, "version", None), "hip", None))
+pass
+
+@functools.cache
+def get_device_type():
+    if hasattr(torch, "cuda") and torch.cuda.is_available():
+        if is_hip():
+            return "hip"
+        return "cuda"
+    elif hasattr(torch, "xpu") and torch.xpu.is_available():
+        return "xpu"
+    # Check torch.accelerator
+    if hasattr(torch, "accelerator"):
+        if not torch.accelerator.is_available():
+            raise NotImplementedError("Unsloth cannot find any torch accelerator? You need a GPU.")
+        accelerator = str(torch.accelerator.current_accelerator())
+        if accelerator in ("cuda", "xpu", "hip"):
+            raise RuntimeError(
+                f"Unsloth: Weirdly `torch.cuda.is_available()`, `torch.xpu.is_available()` and `is_hip` all failed.\n"\
+                f"But `torch.accelerator.current_accelerator()` works with it being = `{accelerator}`\n"\
+                f"Please reinstall torch - it's most likely broken :("
+            )
+    raise NotImplementedError("Unsloth currently only works on NVIDIA, AMD and Intel GPUs.")
+pass
+DEVICE_TYPE : str = get_device_type()
+# HIP fails for autocast and other torch functions. Use CUDA instead
+DEVICE_TYPE_TORCH = DEVICE_TYPE
+if DEVICE_TYPE_TORCH == "hip": DEVICE_TYPE_TORCH = "cuda"
+
+@functools.cache
+def get_device_count():
+    if DEVICE_TYPE in ("cuda", "hip"):
+        return torch.cuda.device_count()
+    elif DEVICE_TYPE == "xpu":
+        return torch.xpu.device_count()
+    else:
+        return 1
+pass
+
+DEVICE_COUNT : int = get_device_count()
+
+# Check blocksize for 4bit -> 64 for CUDA, 128 for AMD
+# If AMD, we cannot load pre-quantized models for now :(
+ALLOW_PREQUANTIZED_MODELS : bool = True
+if DEVICE_TYPE == "hip":
+    try:
+        from bitsandbytes.nn.modules import Params4bit
+        if "blocksize = 64 if not HIP_ENVIRONMENT else 128" in inspect.getsource(Params4bit):
+            ALLOW_PREQUANTIZED_MODELS = False
+    except:
+        pass
+pass

unsloth/kernels/utils.py

@@ -19,7 +19,14 @@
 import functools
 from typing import Optional
 
-from .. import DEVICE_TYPE, DEVICE_COUNT
+from ..device_type import (
+    is_hip,
+    get_device_type,
+    DEVICE_TYPE,
+    DEVICE_TYPE_TORCH,
+    DEVICE_COUNT,
+    ALLOW_PREQUANTIZED_MODELS,
+)
 from .fp8 import weight_dequant, fp8_linear
 
 # torch.cuda.amp.custom_fwd is deprecated >= 2.4

unsloth/models/_utils.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-__version__ = "2025.10.4"
+__version__ = "2025.10.5"
 
 __all__ = [
     "SUPPORTS_BFLOAT16",
@@ -87,7 +87,14 @@
 import warnings, subprocess, re, inspect, psutil, os, math
 from unsloth_zoo.utils import Version
 from importlib.metadata import version as importlib_version
-from unsloth import DEVICE_TYPE, DEVICE_COUNT, DEVICE_TYPE_TORCH
+from ..device_type import (
+    is_hip,
+    get_device_type,
+    DEVICE_TYPE,
+    DEVICE_TYPE_TORCH,
+    DEVICE_COUNT,
+    ALLOW_PREQUANTIZED_MODELS,
+)
 from unsloth_zoo.log import logger
 from unsloth_zoo.tokenizer_utils import (
     patch_tokenizer as _patch_tokenizer,
@@ -1331,6 +1338,7 @@ def _unsloth_pre_compute_loss(self, model, inputs, *args, **kwargs):
 
 def patch_gradient_accumulation_fix(Trainer):
     # Fixes gradient accumulation
+    # Fixes Output 0 of UnslothFusedLossBackward is a view and is being modified inplace.
     import inspect
     if hasattr(Trainer, "get_batch_samples"):
         if Trainer.get_batch_samples.__name__ == "_unsloth_get_batch_samples": return
@@ -1346,6 +1354,32 @@ def patch_gradient_accumulation_fix(Trainer):
 
             # Also fix passing in num_items_in_batch
             if not hasattr(Trainer, "_old_compute_loss"):
+
+                # Fix transformers 4.57.0 causing `Output 0 of UnslothFusedLossBackward is a view and is being modified inplace.`
+                function = inspect.getsource(Trainer.compute_loss)
+                if "loss *=" in function or "loss*=" in function:
+                    where = function.find("def")
+                    function = function.split("\n")
+                    function = "\n".join(x[where:] for x in function)
+
+                    # Import all variables that need importing
+                    import transformers.trainer
+                    items_in_trainer = dir(transformers.trainer)
+                    good_items = []
+                    for item in items_in_trainer:
+                        if item in function: good_items.append(item)
+                    pass
+                    exec("from transformers.trainer import (" + ", ".join(x for x in good_items) + ")", globals())
+
+                    # Replace loss*= with loss = loss *
+                    function = re.sub(
+                        r"loss[\s]{0,}\*\=",
+                        "loss = loss *",
+                        function,
+                    )
+                    exec(function, globals())
+                    Trainer.compute_loss = compute_loss
+                pass
                 Trainer._old_compute_loss = Trainer.compute_loss
                 Trainer.compute_loss = _unsloth_pre_compute_loss
             pass

unsloth/models/llama.py

@@ -27,7 +27,14 @@
 from unsloth_zoo.utils import Version, _get_dtype
 from unsloth_zoo.hf_utils import dtype_from_config, add_dtype_kwargs, fix_lora_auto_mapping
 from unsloth_zoo.peft_utils import SKIP_QUANTIZATION_MODULES
-from unsloth import DEVICE_TYPE, DEVICE_COUNT, DEVICE_TYPE_TORCH
+from ..device_type import (
+    is_hip,
+    get_device_type,
+    DEVICE_TYPE,
+    DEVICE_TYPE_TORCH,
+    DEVICE_COUNT,
+    ALLOW_PREQUANTIZED_MODELS,
+)
 
 transformers_version = Version(transformers_version)
 # Transformers moved rotary embeddings out of all attention layers

unsloth/models/loader.py

@@ -45,6 +45,14 @@
 pass
 from huggingface_hub import HfFileSystem
 import importlib.util
+from ..device_type import (
+    is_hip,
+    get_device_type,
+    DEVICE_TYPE,
+    DEVICE_TYPE_TORCH,
+    DEVICE_COUNT,
+    ALLOW_PREQUANTIZED_MODELS,
+)
 
 # https://github.com/huggingface/transformers/pull/26037 allows 4 bit loading!
 from unsloth_zoo.utils import Version, _get_dtype
@@ -195,6 +203,12 @@ def from_pretrained(
         old_model_name = model_name
         if not use_exact_model_name:
             model_name = get_model_name(model_name, load_in_4bit)
+        # Check if pre-quantized models are allowed
+        # For eg AMD GPUs need blocksize = 128, but our pre-quants are blocksize = 64
+        if not ALLOW_PREQUANTIZED_MODELS and model_name.endswith(("-unsloth-bnb-4bit", "-bnb-4bit")):
+            model_name = model_name.removesuffix("-unsloth-bnb-4bit")
+            model_name = model_name.removesuffix("-bnb-4bit")
+        pass
 
         if USE_MODELSCOPE and not os.path.exists(model_name):
             from modelscope import snapshot_download
@@ -306,6 +320,12 @@ def from_pretrained(
             model_name = peft_config.base_model_name_or_path
             if not use_exact_model_name:
                 model_name = get_model_name(model_name, load_in_4bit)
+            # Check if pre-quantized models are allowed
+            # For eg AMD GPUs need blocksize = 128, but our pre-quants are blocksize = 64
+            if not ALLOW_PREQUANTIZED_MODELS and model_name.endswith(("-unsloth-bnb-4bit", "-bnb-4bit")):
+                model_name = model_name.removesuffix("-unsloth-bnb-4bit")
+                model_name = model_name.removesuffix("-bnb-4bit")
+            pass
             model_config = AutoConfig.from_pretrained(
                 model_name,
                 token = token,
@@ -618,6 +638,12 @@ def from_pretrained(
         old_model_name = model_name
         if not use_exact_model_name:
             model_name = get_model_name(model_name, load_in_4bit)
+        # Check if pre-quantized models are allowed
+        # For eg AMD GPUs need blocksize = 128, but our pre-quants are blocksize = 64
+        if not ALLOW_PREQUANTIZED_MODELS and model_name.endswith(("-unsloth-bnb-4bit", "-bnb-4bit")):
+            model_name = model_name.removesuffix("-unsloth-bnb-4bit")
+            model_name = model_name.removesuffix("-bnb-4bit")
+        pass
 
         # Check modelscope
         if USE_MODELSCOPE and not os.path.exists(model_name):
@@ -833,7 +859,12 @@ def from_pretrained(
             model_name = peft_config.base_model_name_or_path
             if not use_exact_model_name:
                 model_name = get_model_name(model_name, load_in_4bit)
-
+            # Check if pre-quantized models are allowed
+            # For eg AMD GPUs need blocksize = 128, but our pre-quants are blocksize = 64
+            if not ALLOW_PREQUANTIZED_MODELS and model_name.endswith(("-unsloth-bnb-4bit", "-bnb-4bit")):
+                model_name = model_name.removesuffix("-unsloth-bnb-4bit")
+                model_name = model_name.removesuffix("-bnb-4bit")
+            pass
             model_config = AutoConfig.from_pretrained(
                 model_name,
                 token = token,