Merge branch 'main' into nightly
This commit is contained in:
Daniel Han
commit
eddea2f9d4
4 changed files with 14 additions and 17 deletions
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@ -1,6 +1,6 @@
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repos:
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- repo: https://github.com/astral-sh/ruff-pre-commit
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rev: v0.14.8
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rev: v0.14.9
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hooks:
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- id: ruff
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args:
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@ -51,8 +51,8 @@ Use our official [Unsloth Docker image](https://hub.docker.com/r/unsloth/unsloth
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For RTX 50x, B200, 6000 GPUs: `pip install unsloth`. Read our [Blackwell Guide](https://docs.unsloth.ai/basics/training-llms-with-blackwell-rtx-50-series-and-unsloth) and [DGX Spark Guide](https://docs.unsloth.ai/new/fine-tuning-llms-with-nvidia-dgx-spark-and-unsloth) for more details.
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## 🦥 Unsloth News
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- New RoPE & MLP **Triton Kernels** & **Auto Packing**: 3x faster training & 30% less VRAM. [Blog](https://docs.unsloth.ai/new/3x-faster-training-packing)
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- **Ministral 3** by Mistral: Run Ministral 3 or fine-tune with our vision or RL sodoku notebook. [Guide](https://docs.unsloth.ai/new/ministral-3) • [Notebooks](https://docs.unsloth.ai/new/ministral-3#fine-tuningb)
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- New RoPE & MLP **Triton Kernels** & **Padding Free + Packing**: 3x faster training & 30% less VRAM. [Blog](https://docs.unsloth.ai/new/3x-faster-training-packing)
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- **Ministral 3** by Mistral: Run Ministral 3 or fine-tune with vision/RL sodoku notebooks. [Guide](https://docs.unsloth.ai/new/ministral-3) • [Notebooks](https://docs.unsloth.ai/new/ministral-3#fine-tuningb)
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- **500K Context**: Training a 20B model with >500K context is now possible on an 80GB GPU. [Blog](https://docs.unsloth.ai/new/500k-context-length-fine-tuning)
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- **FP8 Reinforcement Learning**: You can now do FP8 GRPO on consumer GPUs. [Blog](https://docs.unsloth.ai/new/fp8-reinforcement-learning) • [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Qwen3_8B_FP8_GRPO.ipynb)
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- **DeepSeek-OCR**: Fine-tune to improve language understanding by 89%. [Guide](https://docs.unsloth.ai/new/deepseek-ocr-run-and-fine-tune) • [Notebook](https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Deepseek_OCR_(3B).ipynb)
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@ -19,8 +19,16 @@ from importlib.metadata import version as importlib_version
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from packaging.version import Version as TrueVersion
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import re
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import logging
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# Cannot import logger here since it'll import transformers
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# from unsloth_zoo.log import logger
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# We cannot do from unsloth_zoo.log import logger since FBGEMM might cause seg faults.
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UNSLOTH_ENABLE_LOGGING = os.environ.get("UNSLOTH_ENABLE_LOGGING", "0") in ("1", "True", "true",)
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logger = logging.getLogger(__name__)
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if UNSLOTH_ENABLE_LOGGING:
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logging.basicConfig(level = logging.INFO, format = '[%(name)s|%(levelname)s]%(message)s')
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logger.setLevel(logging.INFO)
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else:
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logging.basicConfig(level = logging.WARNING, format = '[%(name)s|%(levelname)s]%(message)s')
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logger.setLevel(logging.WARNING)
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def Version(version):
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@ -70,8 +78,6 @@ def fix_message_factory_issue():
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def GetPrototype(self, *args, **kwargs):
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return
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from unsloth_zoo.log import logger
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if not hasattr(google.protobuf.message_factory, "MessageFactory"):
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logger.info("Unsloth: Patching protobuf.MessageFactory as it doesn't exist")
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google.protobuf.message_factory.MessageFactory = MessageFactory
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@ -109,8 +115,6 @@ def fix_xformers_performance_issue():
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return
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xformers_version = importlib_version("xformers")
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if Version(xformers_version) < Version("0.0.29"):
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from unsloth_zoo.log import logger
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xformers_location = importlib.util.find_spec("xformers").origin
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xformers_location = os.path.split(xformers_location)[0]
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cutlass = Path(xformers_location) / "ops" / "fmha" / "cutlass.py"
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@ -140,8 +144,6 @@ def fix_vllm_aimv2_issue():
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return
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vllm_version = importlib_version("vllm")
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if Version(vllm_version) < Version("0.10.1"):
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from unsloth_zoo.log import logger
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vllm_version = importlib.util.find_spec("vllm").origin
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vllm_version = os.path.split(vllm_version)[0]
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ovis_config = Path(vllm_version) / "transformers_utils" / "configs" / "ovis.py"
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@ -273,7 +275,6 @@ def check_fbgemm_gpu_version():
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raise ImportError(
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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!"
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)
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from unsloth_zoo.log import logger
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logger.info(f"Unsloth: fbgemm_gpu_genai=={fbgemm_gpu_version} detected.")
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@ -336,7 +337,6 @@ def patch_enable_input_require_grads():
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self._require_grads_hook = hooks[0]
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PreTrainedModel.enable_input_require_grads = _patched_enable_input_require_grads
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from unsloth_zoo.log import logger
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logger.info(
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"Unsloth: Patched enable_input_require_grads for vision model compatibility"
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@ -378,7 +378,6 @@ def torchvision_compatibility_check():
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f"but found torchvision=={torchvision_version}. "
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f"Please refer to https://pytorch.org/get-started/previous-versions/ for more information."
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)
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from unsloth_zoo.log import logger
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logger.info(
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f"Unsloth: torch=={torch_version} and torchvision=={torchvision_version} are compatible."
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@ -394,7 +393,6 @@ def fix_openenv_no_vllm():
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openenv = Path(trl_location) / "experimental" / "openenv" / "utils.py"
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if not openenv.exists():
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return
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from unsloth_zoo.log import logger
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try:
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with open(openenv, "r+", encoding = "utf-8") as f:
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@ -741,6 +741,7 @@ def _patch_trl_rl_trainers(trainer_file = "grpo_trainer"):
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"generation_kwargs": {},
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"bf16": False,
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"fp16": False,
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"report_to" : "none",
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"include_tokens_per_second": False,
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"include_num_input_tokens_seen": False,
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"auto_find_batch_size": False, # Auto /2 batch size - too many people complained so removing
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@ -907,8 +908,6 @@ def _patch_trl_rl_trainers(trainer_file = "grpo_trainer"):
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for process_extra_arg in process_extra_args:
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extra_args += process_extra_arg(old_RLTrainer_source, old_RLConfig_source)
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# Edit report_to and default it to nothing if max_steps is like 60
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# Create RLConfig args
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extra_args = extra_args.split("\n")
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extra_args = "\n".join(" " * 8 + x for x in extra_args)
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