LocalAI/examples/e2e-fine-tuning/notebook.ipynb

Finetuning a model and using it with LocalAI

This is an example of fine-tuning a LLM model to use with LocalAI written by @mudler.

Specifically, this example shows how to use axolotl to fine-tune a LLM model to consume with LocalAI as a gguf model.

Important!

Before starting, make sure you have selected GPU runtime : Runtime -> Change runtime type -> GPU (T4)!

Change the model to link to your dataset. Upload the dataset as output.jsonl in the root tree and edit the model file (model.yml) with:

# local
datasets:
  - path: /content/output.jsonl
    ds_type: json
    type: completion

A full example:

base_model: openlm-research/open_llama_3b_v2
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
push_dataset_to_hub: false
datasets:
  - path: /content/output.jsonl
    ds_type: json
    type: completion
dataset_prepared_path:
val_set_size: 0.05
adapter: qlora
lora_model_dir:
sequence_len: 1024
sample_packing: true
lora_r: 8
lora_alpha: 32
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:
output_dir: ./qlora-out
gradient_accumulation_steps: 1
micro_batch_size: 2
num_epochs: 4
optimizer: paged_adamw_32bit
torchdistx_path:
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: false
fp16: true
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: false
gptq_groupsize:
gptq_model_v1:
warmup_steps: 20
eval_steps: 0.05
save_steps:
debug:
deepspeed:
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"

In [1]:

# Install axolotl
!git clone https://github.com/OpenAccess-AI-Collective/axolotl  && cd axolotl && git checkout 797f3dd1de8fd8c0eafbd1c9fdb172abd9ff840a #0.3.0
!cd axolotl
!pip install packaging
!cd axolotl && pip install -e '.[flash-attn,deepspeed]'

Cloning into 'axolotl'...
remote: Enumerating objects: 7525, done.
remote: Counting objects: 100% (1726/1726), done.
remote: Compressing objects: 100% (385/385), done.
remote: Total 7525 (delta 1525), reused 1409 (delta 1319), pack-reused 5799
Receiving objects: 100% (7525/7525), 2.64 MiB | 10.52 MiB/s, done.
Resolving deltas: 100% (4854/4854), done.
Note: switching to '797f3dd1de8fd8c0eafbd1c9fdb172abd9ff840a'.

You are in 'detached HEAD' state. You can look around, make experimental
changes and commit them, and you can discard any commits you make in this
state without impacting any branches by switching back to a branch.

If you want to create a new branch to retain commits you create, you may
do so (now or later) by using -c with the switch command. Example:

  git switch -c <new-branch-name>

Or undo this operation with:

  git switch -

Turn off this advice by setting config variable advice.detachedHead to false

HEAD is now at 797f3dd don't train if eval split is too small (#873)
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Collecting starlette<0.28.0,>=0.27.0 (from fastapi->fschat==0.2.29->axolotl==0.3.0)
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Collecting wavedrom (from markdown2[all]->fschat==0.2.29->axolotl==0.3.0)
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[?25h  Preparing metadata (setup.py) ... [?25l[?25hdone
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Collecting jmespath<2.0.0,>=0.7.1 (from botocore<1.31.18,>=1.31.17->aiobotocore~=2.5.4->s3fs->axolotl==0.3.0)
  Downloading jmespath-1.0.1-py3-none-any.whl (20 kB)
Collecting urllib3<3,>=1.21.1 (from requests->bert-score==0.3.13->axolotl==0.3.0)
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[?25hCollecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->GitPython!=3.1.29,>=1.0.0->wandb->axolotl==0.3.0)
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Collecting svgwrite (from wavedrom->markdown2[all]->fschat==0.2.29->axolotl==0.3.0)
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[?25hBuilding wheels for collected packages: optimum, rouge-score, flash-attn, deepspeed, fire, ffmpy, wavedrom, lit
  Building wheel for optimum (pyproject.toml) ... [?25l[?25hdone
  Created wheel for optimum: filename=optimum-1.13.2-py3-none-any.whl size=395598 sha256=c50241754999443c85c875c140c77aa5bf3a40f56a5ffd196d1f3c5199609431
  Stored in directory: /root/.cache/pip/wheels/6e/b7/2c/79405d98f0943373d8546daeae25a3d377f7659ca0cbe48699
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  Created wheel for rouge-score: filename=rouge_score-0.1.2-py3-none-any.whl size=24933 sha256=cc9084a7eefdb136724effd732f6cb7c0fd01f0d7c9e7852043f1cd1d23b45a9
  Stored in directory: /root/.cache/pip/wheels/5f/dd/89/461065a73be61a532ff8599a28e9beef17985c9e9c31e541b4
  Building wheel for flash-attn (setup.py) ... [?25l[?25hdone
  Created wheel for flash-attn: filename=flash_attn-2.3.3-cp310-cp310-linux_x86_64.whl size=57075008 sha256=bcb63b64213ab61590b340b77de84e448a442e19c100480895194df39ad7673d
  Stored in directory: /root/.cache/pip/wheels/e5/e6/fa/941802ec61d1afd320d27160ab1db98e6dba65381f84b76d4a
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  Building wheel for ffmpy (setup.py) ... [?25l[?25hdone
  Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5579 sha256=dd713b1fe6d28ec101c96dbf7033241901635fcddd42a07d9e97fafada70eca4
  Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf
  Building wheel for wavedrom (setup.py) ... [?25l[?25hdone
  Created wheel for wavedrom: filename=wavedrom-2.0.3.post3-py2.py3-none-any.whl size=30053 sha256=65b629500b343fc851f1c23dd2065fa414153974ae25603bba9f99e559ecbf8c
  Stored in directory: /root/.cache/pip/wheels/9c/52/8c/38b454b42f712f325e26f633287484c7dc1ad469e1580c5954
  Building wheel for lit (pyproject.toml) ... [?25l[?25hdone
  Created wheel for lit: filename=lit-17.0.5-py3-none-any.whl size=93256 sha256=209fa0a842c16d9479d3626694714ebd0b9f4afaaacf487e3fb92d19ecfa9fcf
  Stored in directory: /root/.cache/pip/wheels/1c/87/8e/5a42c0d4be23362b68bbff33b17f3c35a3df44f1cd2f5a24b4
Successfully built optimum rouge-score flash-attn deepspeed fire ffmpy wavedrom lit
Installing collected packages: sentencepiece, pydub, ninja, nh3, lit, hjson, ffmpy, bitsandbytes, addict, websockets, urllib3, typing-extensions, svgwrite, smmap, shortuuid, setproctitle, semantic-version, rouge, python-multipart, pynvml, pyarrow-hotfix, orjson, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, numpy, markdown2, jmespath, humanfriendly, hf_transfer, h11, fire, einops, docker-pycreds, dill, colorama, art, aioitertools, aiofiles, wavedrom, uvicorn, starlette, sentry-sdk, rouge-score, nvidia-cusolver-cu11, nvidia-cudnn-cu11, multiprocess, httpcore, gitdb, gekko, coloredlogs, botocore, tiktoken, responses, huggingface-hub, httpx, GitPython, fastapi, aiobotocore, wandb, tokenizers, s3fs, gradio-client, fschat, datasets, transformers, gradio, evaluate, triton, torch, accelerate, peft, xformers, optimum, bert-score, auto-gptq, flash-attn, deepspeed, axolotl
  Attempting uninstall: urllib3
    Found existing installation: urllib3 2.0.7
    Uninstalling urllib3-2.0.7:
      Successfully uninstalled urllib3-2.0.7
  Attempting uninstall: typing-extensions
    Found existing installation: typing_extensions 4.5.0
    Uninstalling typing_extensions-4.5.0:
      Successfully uninstalled typing_extensions-4.5.0
  Attempting uninstall: numpy
    Found existing installation: numpy 1.23.5
    Uninstalling numpy-1.23.5:
      Successfully uninstalled numpy-1.23.5
  Attempting uninstall: huggingface-hub
    Found existing installation: huggingface-hub 0.19.3
    Uninstalling huggingface-hub-0.19.3:
      Successfully uninstalled huggingface-hub-0.19.3
  Attempting uninstall: tokenizers
    Found existing installation: tokenizers 0.15.0
    Uninstalling tokenizers-0.15.0:
      Successfully uninstalled tokenizers-0.15.0
  Attempting uninstall: transformers
    Found existing installation: transformers 4.35.2
    Uninstalling transformers-4.35.2:
      Successfully uninstalled transformers-4.35.2
  Attempting uninstall: triton
    Found existing installation: triton 2.1.0
    Uninstalling triton-2.1.0:
      Successfully uninstalled triton-2.1.0
  Attempting uninstall: torch
    Found existing installation: torch 2.1.0+cu118
    Uninstalling torch-2.1.0+cu118:
      Successfully uninstalled torch-2.1.0+cu118
  Running setup.py develop for axolotl
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
lida 0.0.10 requires kaleido, which is not installed.
llmx 0.0.15a0 requires cohere, which is not installed.
llmx 0.0.15a0 requires openai, which is not installed.
cupy-cuda11x 11.0.0 requires numpy<1.26,>=1.20, but you have numpy 1.26.2 which is incompatible.
tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.8.0 which is incompatible.
torchaudio 2.1.0+cu118 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.
torchdata 0.7.0 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.
torchtext 0.16.0 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.
torchvision 0.16.0+cu118 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.
Successfully installed GitPython-3.1.40 accelerate-0.24.1 addict-2.4.0 aiobotocore-2.5.4 aiofiles-23.2.1 aioitertools-0.11.0 art-6.1 auto-gptq-0.5.1 axolotl-0.3.0 bert-score-0.3.13 bitsandbytes-0.41.2.post2 botocore-1.31.17 colorama-0.4.6 coloredlogs-15.0.1 datasets-2.14.7 deepspeed-0.12.3 dill-0.3.7 docker-pycreds-0.4.0 einops-0.7.0 evaluate-0.4.0 fastapi-0.104.1 ffmpy-0.3.1 fire-0.5.0 flash-attn-2.3.3 fschat-0.2.29 gekko-1.0.6 gitdb-4.0.11 gradio-3.50.2 gradio-client-0.6.1 h11-0.14.0 hf_transfer-0.1.4 hjson-3.1.0 httpcore-1.0.2 httpx-0.25.1 huggingface-hub-0.17.3 humanfriendly-10.0 jmespath-1.0.1 lit-17.0.5 markdown2-2.4.10 multiprocess-0.70.15 nh3-0.2.14 ninja-1.11.1.1 numpy-1.26.2 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 optimum-1.13.2 orjson-3.9.10 peft-0.6.0 pyarrow-hotfix-0.5 pydub-0.25.1 pynvml-11.5.0 python-multipart-0.0.6 responses-0.18.0 rouge-1.0.1 rouge-score-0.1.2 s3fs-2023.6.0 semantic-version-2.10.0 sentencepiece-0.1.99 sentry-sdk-1.35.0 setproctitle-1.3.3 shortuuid-1.0.11 smmap-5.0.1 starlette-0.27.0 svgwrite-1.4.3 tiktoken-0.5.1 tokenizers-0.14.1 torch-2.0.1 transformers-4.35.1 triton-2.0.0 typing-extensions-4.8.0 urllib3-1.26.18 uvicorn-0.24.0.post1 wandb-0.16.0 wavedrom-2.0.3.post3 websockets-11.0.3 xformers-0.0.22

In [2]:

!accelerate config default

accelerate configuration saved at /root/.cache/huggingface/accelerate/default_config.yaml

In [3]:

!pip install accelerate bitsandbytes
!pwd

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/content

In [4]:

import torch
torch.cuda.is_available()

Out [4]:

True

In [5]:

!pip install --upgrade transformers

Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.35.1)
Collecting transformers
  Downloading transformers-4.35.2-py3-none-any.whl (7.9 MB)
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Installing collected packages: transformers
  Attempting uninstall: transformers
    Found existing installation: transformers 4.35.1
    Uninstalling transformers-4.35.1:
      Successfully uninstalled transformers-4.35.1
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
axolotl 0.3.0 requires transformers==4.35.1, but you have transformers 4.35.2 which is incompatible.
Successfully installed transformers-4.35.2

In [6]:

# https://github.com/oobabooga/text-generation-webui/issues/4238
!pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.3.0/flash_attn-2.3.0+cu117torch2.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl

Collecting flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE
  Downloading https://github.com/Dao-AILab/flash-attention/releases/download/v2.3.0/flash_attn-2.3.0+cu117torch2.0cxx11abiFALSE-cp310-cp310-linux_x86_64.whl (30.0 MB)
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[?25hRequirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from flash-attn==2.3.0+cu117torch2.0cxx11abiFALSE) (2.0.1)
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Installing collected packages: flash-attn
  Attempting uninstall: flash-attn
    Found existing installation: flash-attn 2.3.3
    Uninstalling flash-attn-2.3.3:
      Successfully uninstalled flash-attn-2.3.3
Successfully installed flash-attn-2.3.0

Start the training process (fine-tuning)

In [ ]:

!accelerate launch -m axolotl.cli.train model.yml --load_in_8bit=False

2023-11-18 10:15:30.581758: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2023-11-18 10:15:30.581829: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2023-11-18 10:15:30.581870: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2023-11-18 10:15:32.302565: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
/usr/local/lib/python3.10/dist-packages/transformers/deepspeed.py:23: FutureWarning: transformers.deepspeed module is deprecated and will be removed in a future version. Please import deepspeed modules directly from transformers.integrations
  warnings.warn(
                                 dP            dP   dP 
                                 88            88   88 
      .d8888b. dP.  .dP .d8888b. 88 .d8888b. d8888P 88 
      88'  `88  `8bd8'  88'  `88 88 88'  `88   88   88 
      88.  .88  .d88b.  88.  .88 88 88.  .88   88   88 
      `88888P8 dP'  `dP `88888P' dP `88888P'   dP   dP 
                                                       
                                                       

[2023-11-18 10:15:36,028] [WARNING] [axolotl.validate_config:169] [PID:4655] [RANK:0] eval_batch_size != micro_batch_size. This can lead to VRAM instability.
[2023-11-18 10:15:36,239] [INFO] [axolotl.normalize_config:128] [PID:4655] [RANK:0] GPU memory usage baseline: 0.000GB (+0.255GB misc)
[2023-11-18 10:15:36,239] [WARNING] [axolotl.scripts.check_accelerate_default_config:343] [PID:4655] [RANK:0] accelerate config file found at /root/.cache/huggingface/accelerate/default_config.yaml. This can lead to unexpected errors
[2023-11-18 10:15:36,239] [WARNING] [axolotl.scripts.check_user_token:355] [PID:4655] [RANK:0] Error verifying HuggingFace token. Remember to log in using `huggingface-cli login` and get your access token from https://huggingface.co/settings/tokens if you want to use gated models or datasets.
[2023-11-18 10:15:36,594] [DEBUG] [axolotl.load_tokenizer:100] [PID:4655] [RANK:0] EOS: 2 / </s>
[2023-11-18 10:15:36,595] [DEBUG] [axolotl.load_tokenizer:101] [PID:4655] [RANK:0] BOS: 1 / <s>
[2023-11-18 10:15:36,595] [DEBUG] [axolotl.load_tokenizer:102] [PID:4655] [RANK:0] PAD: 0 / <unk>
[2023-11-18 10:15:36,595] [DEBUG] [axolotl.load_tokenizer:103] [PID:4655] [RANK:0] UNK: 0 / <unk>
[2023-11-18 10:15:36,595] [INFO] [axolotl.load_tokenized_prepared_datasets:147] [PID:4655] [RANK:0] Unable to find prepared dataset in last_run_prepared/5dca4483042d16053f3cd9eeaf5ac8af
[2023-11-18 10:15:36,595] [INFO] [axolotl.load_tokenized_prepared_datasets:148] [PID:4655] [RANK:0] Loading raw datasets...
[2023-11-18 10:15:36,595] [INFO] [axolotl.load_tokenized_prepared_datasets:153] [PID:4655] [RANK:0] No seed provided, using default seed of 42
Map (num_proc=2): 100% 846/846 [00:00<00:00, 991.41 examples/s] 
[2023-11-18 10:15:37,890] [INFO] [axolotl.load_tokenized_prepared_datasets:355] [PID:4655] [RANK:0] merging datasets
[2023-11-18 10:15:37,892] [INFO] [axolotl.load_tokenized_prepared_datasets:362] [PID:4655] [RANK:0] Saving merged prepared dataset to disk... last_run_prepared/5dca4483042d16053f3cd9eeaf5ac8af
Saving the dataset (1/1 shards): 100% 846/846 [00:00<00:00, 118881.71 examples/s]
Filter (num_proc=2): 100% 803/803 [00:00<00:00, 3171.26 examples/s]
Filter (num_proc=2): 100% 43/43 [00:00<00:00, 301.68 examples/s]
Map (num_proc=2): 100% 803/803 [00:00<00:00, 2783.35 examples/s]
[2023-11-18 10:15:38,745] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] total_num_tokens: 77893
[2023-11-18 10:15:38,753] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] `total_supervised_tokens: 77893`
[2023-11-18 10:15:44,265] [INFO] [axolotl.utils.samplers.multipack._len_est:178] [PID:4655] [RANK:0] packing_efficiency_estimate: 1.0 total_num_tokens per device: 77893
[2023-11-18 10:15:44,265] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] data_loader_len: 8
[2023-11-18 10:15:44,265] [INFO] [axolotl.log:60] [PID:4655] [RANK:0] sample_packing_eff_est across ranks: [0.95084228515625]
[2023-11-18 10:15:44,265] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] sample_packing_eff_est: 0.96
[2023-11-18 10:15:44,266] [DEBUG] [axolotl.log:60] [PID:4655] [RANK:0] total_num_steps: 32
[2023-11-18 10:15:44,266] [DEBUG] [axolotl.train.log:60] [PID:4655] [RANK:0] loading tokenizer... NousResearch/Llama-2-7b-hf
[2023-11-18 10:15:44,629] [DEBUG] [axolotl.load_tokenizer:100] [PID:4655] [RANK:0] EOS: 2 / </s>
[2023-11-18 10:15:44,629] [DEBUG] [axolotl.load_tokenizer:101] [PID:4655] [RANK:0] BOS: 1 / <s>
[2023-11-18 10:15:44,629] [DEBUG] [axolotl.load_tokenizer:102] [PID:4655] [RANK:0] PAD: 0 / <unk>
[2023-11-18 10:15:44,629] [DEBUG] [axolotl.load_tokenizer:103] [PID:4655] [RANK:0] UNK: 0 / <unk>
[2023-11-18 10:15:44,630] [DEBUG] [axolotl.train.log:60] [PID:4655] [RANK:0] loading model and peft_config...
[2023-11-18 10:15:44,713] [INFO] [axolotl.load_model:201] [PID:4655] [RANK:0] patching _expand_mask
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In [ ]:

!python3 -m axolotl.cli.merge_lora model.yml --lora_model_dir="./qlora-out" --load_in_8bit=False --load_in_4bit=False

In [ ]:

!git clone https://github.com/ggerganov/llama.cpp.git
!cd llama.cpp && make GGML_CUDA=1

In [ ]:

# We need to convert the pytorch model into ggml for quantization
# It crates 'ggml-model-f16.bin' in the 'merged' directory.
!cd llama.cpp && python convert.py --outtype f16 \
    /content/qlora-out/merged/pytorch_model-00001-of-00002.bin

In [ ]:

# Start off by making a basic q4_0 4-bit quantization.
# It's important to have 'ggml' in the name of the quant for some
# software to recognize it's file format.
!cd llama.cpp &&  ./quantize /content/qlora-out/merged/ggml-model-f16.gguf \
    /content/custom-model-q4_0.bin q4_0