unsloth/unsloth/kernels/__init__.py
Daniel Han c33afda563 Nightly (#632)
* 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

---------

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>
2024-06-14 02:58:08 +10:00

40 lines
1.4 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.
from .cross_entropy_loss import fast_cross_entropy_loss
from .rms_layernorm import fast_rms_layernorm
from .rope_embedding import fast_rope_embedding, inplace_rope_embedding
from .swiglu import swiglu_fg_kernel, swiglu_DWf_DW_dfg_kernel
from .geglu import (
geglu_exact_forward_kernel,
geglu_exact_backward_kernel,
geglu_approx_forward_kernel,
geglu_approx_backward_kernel,
)
from .fast_lora import (
get_lora_parameters,
get_lora_parameters_bias,
apply_lora_mlp_swiglu,
apply_lora_mlp_geglu_exact,
apply_lora_mlp_geglu_approx,
apply_lora_qkv,
apply_lora_o,
)
from .utils import fast_dequantize, fast_gemv, QUANT_STATE, fast_linear_forward, matmul_lora
try:
print("🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.")
except:
print("Unsloth: Will patch your computer to enable 2x faster free finetuning.")
pass