Nightly (#676)
* Update llama.py * offload * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * continued pretraining trainer * Update trainer.py * Update trainer.py * Update trainer.py * Update trainer.py * is_bfloat16_supported * Update __init__.py * Update README.md * Update llama.py * is_bfloat16_supported * Update __init__.py * Mistral v3 * Phi 3 medium * Update chat_templates.py * Update chat_templates.py * Phi-3 * Update save.py * Update README.md Mistral v3 to Mistral v0.3 * Untrained tokens * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update llama.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update save.py * Update save.py * Update save.py * checkpoint * Update _utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update llama.py * accelerate * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update tokenizer_utils.py * train_dataloader * Update llama.py * Update llama.py * Update llama.py * use_fast_convert * Update save.py * Update save.py * Update save.py * Update save.py * remove_special_tokens * Ollama * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update llama.py * Update chat_templates.py * Support bfloat16 GGUF * Update save.py * Update llama.py * fast_forward_inference * Update mapper.py * Update loader.py * Update llama.py * Update tokenizer_utils.py * info * edits * Create chat template * Fix tokenizer * Update tokenizer_utils.py * fix case where gguf saving fails due to first_conversion dtype (#630) * Support revision parameter in FastLanguageModel.from_pretrained (#629) * support `revision` parameter * match unsloth formatting of named parameters * clears any selected_adapters before calling internal_model.save_pretrained (#609) * Update __init__.py (#602) Check for incompatible modules before importing unsloth * Fixed unsloth/tokenizer_utils.py for chat training (#604) * Add GGML saving option to Unsloth for easier Ollama model creation and testing. (#345) * Add save to llama.cpp GGML to save.py. * Fix conversion command and path of convert to GGML function. * Add autosaving lora to the GGML function * Create lora save function for conversion to GGML * Test fix #2 for saving lora * Test fix #3 to save the lora adapters to convert to GGML * Remove unwated tokenizer saving for conversion to ggml and added a few print statements. * Needed tokenizer for saving, added it back, also made it more unslothy style by having positional arguments, and added a few messages. * Positional arguments didn't work out, so reverted to older version of the code, and added a few comments. * Test fix 1 for arch * Test fix 2 new Mistral error. * Test fix 3 * Revert to old version for testing. * Upload issue test fix 1 * Fix 2 uploading ggml * Positional ags added. * Temporray remove positional args * Fix upload again!!! * Add print statements and fix link * Make the calling name better * Create local saving for GGML * Add choosing directory to save local GGML. * Fix lil variable error in the save_to_custom_dir func * docs: Add LoraConfig parameters documentation (#619) * llama.cpp failing (#371) llama.cpp is failing to generate quantize versions for the trained models. Error: ```bash You might have to compile llama.cpp yourself, then run this again. You do not need to close this Python program. Run the following commands in a new terminal: You must run this in the same folder as you're saving your model. git clone https://github.com/ggerganov/llama.cpp cd llama.cpp && make clean && LLAMA_CUDA=1 make all -j Once that's done, redo the quantization. ``` But when i do clone this with recursive it works. Co-authored-by: Daniel Han <danielhanchen@gmail.com> * fix libcuda_dirs import for triton 3.0 (#227) * fix libcuda_dirs import for triton 3.0 * Update __init__.py * Update __init__.py --------- Co-authored-by: Daniel Han <danielhanchen@gmail.com> * Update save.py * Update __init__.py * Update fast_lora.py * Update save.py * Update save.py * Update save.py * Update loader.py * Update save.py * Update save.py * quantize now llama-quantize * Update chat_templates.py * Update loader.py * Update mapper.py * Update __init__.py * embedding size * Update qwen2.py * docs * Update README.md * Update qwen2.py * README: Fix minor typo. (#559) * README: Fix minor typo. One-character typo fix while reading. * Update README.md --------- Co-authored-by: Daniel Han <danielhanchen@gmail.com> * Update mistral.py * Update qwen2.py * Update qwen2.py * Update qwen2.py * Update llama.py * Update llama.py * Update llama.py * Update README.md * FastMistralModel * Update mistral.py * Update mistral.py * Update mistral.py * Update mistral.py * Update mistral.py * Auto check rope scaling * Update llama.py * Update llama.py * Update llama.py * GPU support * Typo * Update gemma.py * gpu * Multiple GGUF saving * Update save.py * Update save.py * check PEFT and base * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update chat_templates.py * Fix breaking bug in save.py with interpreting quantization_method as a string when saving to gguf (#651) * Nightly (#649) * Update llama.py * offload * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * continued pretraining trainer * Update trainer.py * Update trainer.py * Update trainer.py * Update trainer.py * is_bfloat16_supported * Update __init__.py * Update README.md * Update llama.py * is_bfloat16_supported * Update __init__.py * Mistral v3 * Phi 3 medium * Update chat_templates.py * Update chat_templates.py * Phi-3 * Update save.py * Update README.md Mistral v3 to Mistral v0.3 * Untrained tokens * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update llama.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update save.py * Update save.py * Update save.py * checkpoint * Update _utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update tokenizer_utils.py * Update llama.py * accelerate * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update _utils.py * Update tokenizer_utils.py * train_dataloader * Update llama.py * Update llama.py * Update llama.py * use_fast_convert * Update save.py * Update save.py * Update save.py * Update save.py * remove_special_tokens * Ollama * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update llama.py * Update chat_templates.py * Support bfloat16 GGUF * Update save.py * Update llama.py * fast_forward_inference * Update mapper.py * Update loader.py * Update llama.py * Update tokenizer_utils.py * info * edits * Create chat template * Fix tokenizer * Update tokenizer_utils.py * fix case where gguf saving fails due to first_conversion dtype (#630) * Support revision parameter in FastLanguageModel.from_pretrained (#629) * support `revision` parameter * match unsloth formatting of named parameters * clears any selected_adapters before calling internal_model.save_pretrained (#609) * Update __init__.py (#602) Check for incompatible modules before importing unsloth * Fixed unsloth/tokenizer_utils.py for chat training (#604) * Add GGML saving option to Unsloth for easier Ollama model creation and testing. (#345) * Add save to llama.cpp GGML to save.py. * Fix conversion command and path of convert to GGML function. * Add autosaving lora to the GGML function * Create lora save function for conversion to GGML * Test fix #2 for saving lora * Test fix #3 to save the lora adapters to convert to GGML * Remove unwated tokenizer saving for conversion to ggml and added a few print statements. * Needed tokenizer for saving, added it back, also made it more unslothy style by having positional arguments, and added a few messages. * Positional arguments didn't work out, so reverted to older version of the code, and added a few comments. * Test fix 1 for arch * Test fix 2 new Mistral error. * Test fix 3 * Revert to old version for testing. * Upload issue test fix 1 * Fix 2 uploading ggml * Positional ags added. * Temporray remove positional args * Fix upload again!!! * Add print statements and fix link * Make the calling name better * Create local saving for GGML * Add choosing directory to save local GGML. * Fix lil variable error in the save_to_custom_dir func * docs: Add LoraConfig parameters documentation (#619) * llama.cpp failing (#371) llama.cpp is failing to generate quantize versions for the trained models. Error: ```bash You might have to compile llama.cpp yourself, then run this again. You do not need to close this Python program. Run the following commands in a new terminal: You must run this in the same folder as you're saving your model. git clone https://github.com/ggerganov/llama.cpp cd llama.cpp && make clean && LLAMA_CUDA=1 make all -j Once that's done, redo the quantization. ``` But when i do clone this with recursive it works. Co-authored-by: Daniel Han <danielhanchen@gmail.com> * fix libcuda_dirs import for triton 3.0 (#227) * fix libcuda_dirs import for triton 3.0 * Update __init__.py * Update __init__.py --------- Co-authored-by: Daniel Han <danielhanchen@gmail.com> * Update save.py * Update __init__.py * Update fast_lora.py * Update save.py * Update save.py * Update save.py * Update loader.py * Update save.py * Update save.py * quantize now llama-quantize * Update chat_templates.py * Update loader.py * Update mapper.py * Update __init__.py * embedding size * Update qwen2.py * docs * Update README.md * Update qwen2.py * README: Fix minor typo. (#559) * README: Fix minor typo. One-character typo fix while reading. * Update README.md --------- Co-authored-by: Daniel Han <danielhanchen@gmail.com> * Update mistral.py * Update qwen2.py * Update qwen2.py * Update qwen2.py * Update llama.py * Update llama.py * Update llama.py * Update README.md * FastMistralModel * Update mistral.py * Update mistral.py * Update mistral.py * Update mistral.py * Update mistral.py * Auto check rope scaling * Update llama.py * Update llama.py * Update llama.py * GPU support * Typo * Update gemma.py * gpu * Multiple GGUF saving * Update save.py * Update save.py * check PEFT and base * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update chat_templates.py --------- Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com> Co-authored-by: Eliot Hall <60240707+chrehall68@users.noreply.github.com> Co-authored-by: Rickard Edén <rickardeden@gmail.com> Co-authored-by: XiaoYang <xyangk@gmail.com> Co-authored-by: Oseltamivir <58582368+Oseltamivir@users.noreply.github.com> Co-authored-by: mahiatlinux <110882203+mahiatlinux@users.noreply.github.com> Co-authored-by: Sébastien De Greef <sebdg@binarycompany.com> Co-authored-by: Alberto Ferrer <albertof@barrahome.org> Co-authored-by: Thomas Viehmann <tv.github-private@beamnet.de> Co-authored-by: Walter Korman <lemurware@gmail.com> * Fix bug in save.py with interpreting quantization_method as a string that prevents GGUF from saving * Implemented better list management and then forgot to actually call the new list variable, fixed * Check type of given quantization method and return type error if not list or string * Update save.py --------- Co-authored-by: Daniel Han <danielhanchen@gmail.com> Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com> Co-authored-by: Eliot Hall <60240707+chrehall68@users.noreply.github.com> Co-authored-by: Rickard Edén <rickardeden@gmail.com> Co-authored-by: XiaoYang <xyangk@gmail.com> Co-authored-by: Oseltamivir <58582368+Oseltamivir@users.noreply.github.com> Co-authored-by: mahiatlinux <110882203+mahiatlinux@users.noreply.github.com> Co-authored-by: Sébastien De Greef <sebdg@binarycompany.com> Co-authored-by: Alberto Ferrer <albertof@barrahome.org> Co-authored-by: Thomas Viehmann <tv.github-private@beamnet.de> Co-authored-by: Walter Korman <lemurware@gmail.com> * Revert "Fix breaking bug in save.py with interpreting quantization_method as …" (#652) This reverts commit 506cb68867296237e95bc53c32f1bfc9b1757960. * Revert "Revert "Fix breaking bug in save.py with interpreting quantization_me…" (#653) This reverts commit 2f48cc9af385579876fd45bd833169d1f1a2ea58. * Update llama.py * peft * patch * Update loader.py * retrain * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * Update llama.py * offload * Update llama.py * Create a starter script for command-line training to integrate in ML ops pipelines. (#623) * Update chat_templates.py * Ollama * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Ollama * Update chat_templates.py * ollama * Update mapper.py * Update chat_templates.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update save.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update chat_templates.py * Update llama.py * Fixes * clearer messages * Update tokenizer_utils.py * Update tokenizer_utils.py * Update llama.py * Update llama.py * Update llama.py * log * Update __init__.py * Update llama.py * Update __init__.py --------- Co-authored-by: Michael Han <107991372+shimmyshimmer@users.noreply.github.com> Co-authored-by: Eliot Hall <60240707+chrehall68@users.noreply.github.com> Co-authored-by: Rickard Edén <rickardeden@gmail.com> Co-authored-by: XiaoYang <xyangk@gmail.com> Co-authored-by: Oseltamivir <58582368+Oseltamivir@users.noreply.github.com> Co-authored-by: mahiatlinux <110882203+mahiatlinux@users.noreply.github.com> Co-authored-by: Sébastien De Greef <sebdg@binarycompany.com> Co-authored-by: Alberto Ferrer <albertof@barrahome.org> Co-authored-by: Thomas Viehmann <tv.github-private@beamnet.de> Co-authored-by: Walter Korman <lemurware@gmail.com> Co-authored-by: ArcadaLabs-Jason <52756218+ArcadaLabs-Jason@users.noreply.github.com>
This commit is contained in:
Daniel Han
GitHub
parent
c19e2e1015
commit
71e5bad518
3 changed files with 47 additions and 34 deletions
|
|
@ -17,17 +17,20 @@ import importlib
|
|||
import sys
|
||||
from packaging.version import Version
|
||||
|
||||
# Define a list of modules to check
|
||||
MODULES_TO_CHECK = ["bitsandbytes"]
|
||||
# # Define a list of modules to check
|
||||
# MODULES_TO_CHECK = ["bitsandbytes"]
|
||||
|
||||
# Check if any of the modules in the list have been imported
|
||||
for module in MODULES_TO_CHECK:
|
||||
if module in sys.modules:
|
||||
raise ImportError(f"Unsloth: Please import Unsloth before {module}.")
|
||||
pass
|
||||
pass
|
||||
# # Check if any of the modules in the list have been imported
|
||||
# for module in MODULES_TO_CHECK:
|
||||
# if module in sys.modules:
|
||||
# raise ImportError(f"Unsloth: Please import Unsloth before {module}.")
|
||||
# pass
|
||||
# pass
|
||||
|
||||
# Currently only supports 1 GPU, or else seg faults will occur.
|
||||
# Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so
|
||||
# enabling it will require much more work, so we have to prioritize. Please understand!
|
||||
# We do have a beta version, which you can contact us about!
|
||||
# Thank you for your understanding and we appreciate it immensely!
|
||||
if "CUDA_VISIBLE_DEVICES" in os.environ:
|
||||
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
|
||||
devices = os.environ["CUDA_VISIBLE_DEVICES"]
|
||||
|
|
@ -36,6 +39,10 @@ if "CUDA_VISIBLE_DEVICES" in os.environ:
|
|||
first_id = devices.split(",")[0]
|
||||
warnings.warn(
|
||||
f"Unsloth: 'CUDA_VISIBLE_DEVICES' is currently {devices} \n"\
|
||||
"Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so "\
|
||||
"enabling it will require much more work, so we have to prioritize. Please understand!"\
|
||||
"We do have a beta version, which you can contact us about!\n"\
|
||||
"Thank you for your understanding and we appreciate it immensely!\n\n"\
|
||||
"Multiple CUDA devices detected but we require a single device.\n"\
|
||||
f"We will override CUDA_VISIBLE_DEVICES to first device: {first_id}."
|
||||
)
|
||||
|
|
|
|||
|
|
@ -1165,10 +1165,10 @@ class FastLlamaModel:
|
|||
inner_training_loop = Trainer._original_training_loop
|
||||
except:
|
||||
raise RuntimeError(
|
||||
"Our OSS was designed for people with few GPU resources to level the playing field.\n"
|
||||
"The OSS Apache 2 license only supports one GPU - please obtain a commercial license.\n"
|
||||
"We're a 2 person team, so we still have to fund our development costs - thanks!\n"
|
||||
"If you don't, please consider at least sponsoring us through Ko-fi! Appreciate it!",
|
||||
'Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so '\
|
||||
'enabling it will require much more work, so we have to prioritize. Please understand!\n'\
|
||||
'We do have a separate beta version, which you can contact us about!\n'\
|
||||
'Thank you for your understanding and we appreciate it immensely!'
|
||||
)
|
||||
pass
|
||||
|
||||
|
|
@ -1201,7 +1201,10 @@ class FastLlamaModel:
|
|||
output = re.findall(rb'([\\d]{1,})[\\s]{1,}M', output)
|
||||
output = sum(int(x.decode('utf-8'))/1024 > 4 for x in output)
|
||||
if output > 1: raise RuntimeError(
|
||||
'Error: More than 1 GPUs have a lot of VRAM usage. Please obtain a commercial license.')
|
||||
'Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so '\\
|
||||
'enabling it will require much more work, so we have to prioritize. Please understand!\\n'\\
|
||||
'We do have a separate beta version, which you can contact us about!\\n'\\
|
||||
'Thank you for your understanding and we appreciate it immensely!')
|
||||
for _ in range(3):
|
||||
gc.collect()
|
||||
torch.cuda.empty_cache()"""
|
||||
|
|
@ -1214,10 +1217,10 @@ class FastLlamaModel:
|
|||
args.gradient_accumulation_steps // self._train_batch_size
|
||||
if n_total_devices > 1:
|
||||
logger.warning_once(
|
||||
"* Our OSS was designed for people with few GPU resources to level the playing field.\\n"
|
||||
"* The OSS Apache 2 license only supports one GPU - please obtain a commercial license.\\n"
|
||||
"* We're a 2 person team, so we still have to fund our development costs - thanks!\\n"
|
||||
"* If you don't, please consider at least sponsoring us through Ko-fi! Appreciate it!",
|
||||
'* Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so ' \\
|
||||
'* enabling it will require much more work, so we have to prioritize. Please understand!\\n' \\
|
||||
'* We do have a separate beta version, which you can contact us about!\\n'\\
|
||||
'* Thank you for your understanding and we appreciate it immensely!'
|
||||
)
|
||||
debug_info ="""
|
||||
debug_info = debug_info.split('\n')
|
||||
|
|
@ -1244,10 +1247,10 @@ class FastLlamaModel:
|
|||
n_total_devices = total_batches // ga // bsz
|
||||
if n_total_devices > 1:
|
||||
logger.warning_once(
|
||||
"* Our OSS was designed for people with few GPU resources to level the playing field.\\n"
|
||||
"* The OSS Apache 2 license only supports one GPU - please obtain a commercial license.\\n"
|
||||
"* We're a 2 person team, so we still have to fund our development costs - thanks!\\n"
|
||||
"* If you don't, please consider at least sponsoring us through Ko-fi! Appreciate it!",
|
||||
'* Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so ' \\
|
||||
'* enabling it will require much more work, so we have to prioritize. Please understand!\\n' \\
|
||||
'* We do have a separate beta version, which you can contact us about!\\n'\\
|
||||
'* Thank you for your understanding and we appreciate it immensely!'
|
||||
)
|
||||
divisor = n_total_devices / 1
|
||||
bsz = self._train_batch_size = max(int(bsz / divisor), 1)
|
||||
|
|
@ -1273,10 +1276,10 @@ class FastLlamaModel:
|
|||
)
|
||||
if "n_total_devices >" not in inner_training_loop:
|
||||
raise RuntimeError(
|
||||
"Our OSS was designed for people with few GPU resources to level the playing field.\n"
|
||||
"The OSS Apache 2 license only supports one GPU - please obtain a commercial license.\n"
|
||||
"We're a 2 person team, so we still have to fund our development costs - thanks!\n"
|
||||
"If you don't, please consider at least sponsoring us through Ko-fi! Appreciate it!",
|
||||
'Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so '\
|
||||
'enabling it will require much more work, so we have to prioritize. Please understand!\n'\
|
||||
'We do have a separate beta version, which you can contact us about!\n'\
|
||||
'Thank you for your understanding and we appreciate it immensely!'
|
||||
)
|
||||
pass
|
||||
inner_training_loop = inner_training_loop.replace(
|
||||
|
|
@ -1783,10 +1786,10 @@ class FastLlamaModel:
|
|||
from transformers.trainer import Trainer
|
||||
if Trainer._inner_training_loop.__name__ != "_fast_inner_training_loop":
|
||||
raise RuntimeError(
|
||||
"Our OSS was designed for people with few GPU resources to level the playing field.\n"
|
||||
"The OSS Apache 2 license only supports one GPU - please obtain a commercial license.\n"
|
||||
"We're a 2 person team, so we still have to fund our development costs - thanks!\n"
|
||||
"If you don't, please consider at least sponsoring us through Ko-fi! Appreciate it!",
|
||||
'Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so '\
|
||||
'enabling it will require much more work, so we have to prioritize. Please understand!\n'\
|
||||
'We do have a separate beta version, which you can contact us about!\n'\
|
||||
'Thank you for your understanding and we appreciate it immensely!'
|
||||
)
|
||||
pass
|
||||
|
||||
|
|
|
|||
|
|
@ -954,7 +954,7 @@ def patch_sft_trainer_tokenizer():
|
|||
"\n"\
|
||||
"if self._inner_training_loop.__name__ != '_fast_inner_training_loop':\n"\
|
||||
" raise RuntimeError(\n"\
|
||||
" 'Do not edit specific areas of the Unsloth codebase or you will get CUDA segfaults.'\n"\
|
||||
" 'Please do not edit specific areas of the Unsloth codebase or you will get CUDA segfaults.'\n"\
|
||||
" )\n"\
|
||||
"pass\n"\
|
||||
"n_devices = torch.cuda.device_count()\n"\
|
||||
|
|
@ -964,7 +964,10 @@ def patch_sft_trainer_tokenizer():
|
|||
"output = re.findall(rb'([\\d]{1,})[\\s]{1,}M', output)\n"\
|
||||
"output = sum(int(x.decode('utf-8'))/1024 > 4 for x in output)\n"\
|
||||
"if output > 1: raise RuntimeError(\n"\
|
||||
" 'Error: More than 1 GPUs have a lot of VRAM usage. Please obtain a commercial license.')\n"\
|
||||
" 'Unsloth currently does not work on multi GPU setups - sadly we are a 2 brother team so '\\\n"\
|
||||
" 'enabling it will require much more work, so we have to prioritize. Please understand!\\n'\\\n"\
|
||||
" 'We do have a separate beta version, which you can contact us about!\\n'\\\n"\
|
||||
" 'Thank you for your understanding and we appreciate it immensely!')\n"\
|
||||
"for _ in range(3):\n"\
|
||||
" gc.collect()\n"\
|
||||
" torch.cuda.empty_cache()\n"\
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue