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fix lint #856

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merged 2 commits into from
Jul 19, 2024
Merged

fix lint #856

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415ad36
fix lint
HIT-cwh Jul 19, 2024
42ae17d
fix lint
HIT-cwh Jul 19, 2024
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2 changes: 1 addition & 1 deletion xtuner/configs/custom_dataset/pretrain/minicpm/minicpm_1b_full_custom_pretrain_e1.py
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Expand Up @@ -36,7 +36,7 @@
use_varlen_attn = False

# Data
data_files = ['/root/ld/pull_request/xtuner/xtuner/configs/custom_dataset/pretrain/minicpm/pretrain.json']
data_files = ['/path/to/json/file.json']
max_length = 2048
pack_to_max_length = True

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2 changes: 1 addition & 1 deletion xtuner/configs/custom_dataset/sft/minicpm/minicpm_1b_full_custom_pretrain_e1.py
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Expand Up @@ -36,7 +36,7 @@
use_varlen_attn = False

# Data
data_files = ['/root/ld/pull_request/xtuner/xtuner/configs/custom_dataset/pretrain/minicpm/pretrain.json']
data_files = ['/path/to/json/file.json']
max_length = 2048
pack_to_max_length = True

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8 changes: 5 additions & 3 deletions xtuner/configs/minicpm/1_2b/minicpm_1b_dpo_qlora.py
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@@ -1,13 +1,15 @@
# Copyright (c) OpenMMLab. All rights reserved.
from datasets import load_dataset
import torch
from datasets import load_dataset
from mmengine.dataset import DefaultSampler
from mmengine.hooks import (CheckpointHook, DistSamplerSeedHook, IterTimerHook,
LoggerHook, ParamSchedulerHook)
from mmengine.optim import AmpOptimWrapper, CosineAnnealingLR, LinearLR
from torch.optim import AdamW
from transformers import AutoModelForCausalLM, AutoTokenizer,BitsAndBytesConfig
from peft import LoraConfig
from torch.optim import AdamW
from transformers import (AutoModelForCausalLM, AutoTokenizer,
BitsAndBytesConfig)

from xtuner.dataset.collate_fns.preference_collate_fn import \
preference_collate_fn
from xtuner.dataset.preference_dataset import (build_preference_dataset,
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5 changes: 2 additions & 3 deletions xtuner/configs/minicpm/1_2b/minicpm_1b_lora_alpaca_zh_e3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,8 +7,7 @@
from mmengine.optim import AmpOptimWrapper, CosineAnnealingLR, LinearLR
from peft import LoraConfig
from torch.optim import AdamW
from transformers import (AutoModelForCausalLM, AutoTokenizer,
BitsAndBytesConfig)
from transformers import AutoModelForCausalLM, AutoTokenizer

from xtuner.dataset import process_hf_dataset
from xtuner.dataset.collate_fns import default_collate_fn
Expand Down Expand Up @@ -78,7 +77,7 @@
pretrained_model_name_or_path=pretrained_model_name_or_path,
trust_remote_code=True,
torch_dtype=torch.float16,
),
),
lora=dict(
type=LoraConfig,
r=64,
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8 changes: 5 additions & 3 deletions xtuner/configs/minicpm/2b/minicpm_2b_dpo_qlora.py
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Original file line number Diff line number Diff line change
@@ -1,13 +1,15 @@
# Copyright (c) OpenMMLab. All rights reserved.
from datasets import load_dataset
import torch
from datasets import load_dataset
from mmengine.dataset import DefaultSampler
from mmengine.hooks import (CheckpointHook, DistSamplerSeedHook, IterTimerHook,
LoggerHook, ParamSchedulerHook)
from mmengine.optim import AmpOptimWrapper, CosineAnnealingLR, LinearLR
from torch.optim import AdamW
from transformers import AutoModelForCausalLM, AutoTokenizer,BitsAndBytesConfig
from peft import LoraConfig
from torch.optim import AdamW
from transformers import (AutoModelForCausalLM, AutoTokenizer,
BitsAndBytesConfig)

from xtuner.dataset.collate_fns.preference_collate_fn import \
preference_collate_fn
from xtuner.dataset.preference_dataset import (build_preference_dataset,
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5 changes: 2 additions & 3 deletions xtuner/configs/minicpm/2b/minicpm_2b_lora_alpaca_zh_e3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,8 +7,7 @@
from mmengine.optim import AmpOptimWrapper, CosineAnnealingLR, LinearLR
from peft import LoraConfig
from torch.optim import AdamW
from transformers import (AutoModelForCausalLM, AutoTokenizer,
BitsAndBytesConfig)
from transformers import AutoModelForCausalLM, AutoTokenizer

from xtuner.dataset import process_hf_dataset
from xtuner.dataset.collate_fns import default_collate_fn
Expand Down Expand Up @@ -78,7 +77,7 @@
pretrained_model_name_or_path=pretrained_model_name_or_path,
trust_remote_code=True,
torch_dtype=torch.float16,
),
),
lora=dict(
type=LoraConfig,
r=64,
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4 changes: 1 addition & 3 deletions xtuner/utils/templates.py
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Expand Up @@ -130,9 +130,7 @@
SYSTEM=('[INST] {system} [/INST]\n'),
INSTRUCTION=('[INST] {input} [/INST]'),
SEP='\n'),
minicpm=dict(
INSTRUCTION=('<用户> {input} <AI>'),
SEP='\n'),
minicpm=dict(INSTRUCTION=('<用户> {input} <AI>'), SEP='\n'),
gemma=dict(
# `system` field is extended by xtuner
SYSTEM=('<start_of_turn>system\n{system}<end_of_turn>\n'),
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