aa086eab6b* Enable FP8 + RL training for bf16 models (#3440) * Enable FP8 + RL training for bf16 models **Summary:** Enable FP8 + RL training using TorchAO for 1.33x faster training and 42% less model memory usage: - We quantize the frozen LoRA weights into fp8 and keep the LoRA adapters in bf16 - We leverage TorchAO's `Float8Tensor`, which calls into fbgemm's fp8 x fp8 rowwise matmul kernel - For now, we need to do an offline quantization first, because vllm doesn't support on-the-fly quantization for torchao yet (this is in progress: https://github.com/vllm-project/vllm/pull/26327) **Example usage:** ``` model, tokenizer = FastLanguageModel.from_pretrained( model_name = "unsloth/Qwen3-8B-Base", max_seq_length = 2048, load_in_4bit = False, fast_inference = True, max_lora_rank = 32, load_in_fp8 = True, # set this to True ) \# the rest is the same as before model = FastLanguageModel.get_peft_model(...) ``` **Initial results:** ``` \# fp8 {'train_runtime': 1725.4337, 'train_samples_per_second': 0.232, 'train_steps_per_second': 0.058, 'train_loss': 0.00015715716748673002, 'epoch': 0.01} \# bf16 {'train_runtime': 2297.8145, 'train_samples_per_second': 0.174, 'train_steps_per_second': 0.044, 'train_loss': 0.00016081033063528594, 'epoch': 0.01} ``` <img width="1199" height="448" alt="Screenshot 2025-11-11 at 4 10 50 PM" src="https://github.com/user-attachments/assets/b6304afd-89e9-42b1-8064-775807e17b23" /> Test script: https://gist.github.com/andrewor14/5b85119fae46845d07b608d420907423 **Requires:** - https://github.com/pytorch/ao/pull/3158 (torchao nightly or 0.15.0+) - https://github.com/unslothai/unsloth-zoo/pull/351 * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update utils.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * _get_inference_mode_context_manager * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update utils.py * Update utils.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Daniel Han <danielhanchen@gmail.com> * Update __init__.py * Fix/save torchao model loading logic (#3621) * make loading gpt-oss-BF16 faster. Linked to unsloth-zoo PR #314 * fix model loading and clean merged model directory * revert default quant * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * revert mapper.py --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * Update loader_utils.py * Update loader_utils.py * Add 128x128 PerBlock FP8 + RL (#3629) * Add 128x128 PerBlock FP8 + RL **Summary:** Following https://github.com/unslothai/unsloth/pull/3440, this PR extends torchao FP8 + RL support to also handle 128x128 PerBlock granularity (in addition to PerRow). **Example usage:** ``` model, tokenizer = FastLanguageModel.from_pretrained( model_name = "unsloth/Qwen3-8B-Base", max_seq_length = 2048, load_in_4bit = False, fast_inference = True, max_lora_rank = 32, load_in_fp8 = "block", # or "row" or True ) ``` **Initial results:** TBD **Note:** - Requires https://github.com/pytorch/ao/pull/3370 * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * Version * Update vision.py * Update rl.py * Add torch 2.9.1 * Fix auto installer * Update fp8.py * Float8 * Update fp8.py * Update mapper.py * Update mapper.py * Update loader_utils.py * Update loader.py * Update fp8.py * Versioning * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: andrewor14 <andrewor14@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
41 lines
No EOL
2.1 KiB
Python
41 lines
No EOL
2.1 KiB
Python
# 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.
|
|
|
|
try: import torch
|
|
except: raise ImportError('Install torch via `pip install torch`')
|
|
from packaging.version import Version as V
|
|
import re
|
|
v = V(re.match(r"[0-9\.]{3,}", torch.__version__).group(0))
|
|
cuda = str(torch.version.cuda)
|
|
is_ampere = torch.cuda.get_device_capability()[0] >= 8
|
|
USE_ABI = torch._C._GLIBCXX_USE_CXX11_ABI
|
|
if cuda not in ("11.8", "12.1", "12.4", "12.6", "12.8", "13.0"): raise RuntimeError(f"CUDA = {cuda} not supported!")
|
|
if v <= V('2.1.0'): raise RuntimeError(f"Torch = {v} too old!")
|
|
elif v <= V('2.1.1'): x = 'cu{}{}-torch211'
|
|
elif v <= V('2.1.2'): x = 'cu{}{}-torch212'
|
|
elif v < V('2.3.0'): x = 'cu{}{}-torch220'
|
|
elif v < V('2.4.0'): x = 'cu{}{}-torch230'
|
|
elif v < V('2.5.0'): x = 'cu{}{}-torch240'
|
|
elif v < V('2.5.1'): x = 'cu{}{}-torch250'
|
|
elif v <= V('2.5.1'): x = 'cu{}{}-torch251'
|
|
elif v < V('2.7.0'): x = 'cu{}{}-torch260'
|
|
elif v < V('2.7.9'): x = 'cu{}{}-torch270'
|
|
elif v < V('2.8.0'): x = 'cu{}{}-torch271'
|
|
elif v < V('2.8.9'): x = 'cu{}{}-torch280'
|
|
elif v < V('2.9.1'): x = 'cu{}{}-torch290'
|
|
elif v < V('2.9.2'): x = 'cu{}{}-torch291'
|
|
else: raise RuntimeError(f"Torch = {v} too new!")
|
|
if v > V('2.6.9') and cuda not in ("11.8", "12.6", "12.8", "13.0"): raise RuntimeError(f"CUDA = {cuda} not supported!")
|
|
x = x.format(cuda.replace(".", ""), "-ampere" if False else "") # is_ampere is broken due to flash-attn
|
|
print(f'pip install --upgrade pip && pip install --no-deps git+https://github.com/unslothai/unsloth-zoo.git && pip install "unsloth[{x}] @ git+https://github.com/unslothai/unsloth.git" --no-build-isolation') |