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ModelZoo
GLM-4V_pytorch
Commits
1bfbcff0
Commit
1bfbcff0
authored
Jun 13, 2024
by
wanglch
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swift-main/examples/pytorch/llm/scripts/qwen_7b_chat_int8/qlora_ddp_ds/sft.sh
...pytorch/llm/scripts/qwen_7b_chat_int8/qlora_ddp_ds/sft.sh
+40
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swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/full_mp/infer.sh
...ples/pytorch/llm/scripts/qwen_audio_chat/full_mp/infer.sh
+6
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swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/full_mp/sft.sh
...amples/pytorch/llm/scripts/qwen_audio_chat/full_mp/sft.sh
+16
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swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/full_mp_ddp/infer.sh
.../pytorch/llm/scripts/qwen_audio_chat/full_mp_ddp/infer.sh
+6
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swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/full_mp_ddp/sft.sh
...es/pytorch/llm/scripts/qwen_audio_chat/full_mp_ddp/sft.sh
+17
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swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/lora/infer.sh
...xamples/pytorch/llm/scripts/qwen_audio_chat/lora/infer.sh
+13
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swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/lora/sft.sh
.../examples/pytorch/llm/scripts/qwen_audio_chat/lora/sft.sh
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swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/lora_ddp_ds/infer.sh
.../pytorch/llm/scripts/qwen_audio_chat/lora_ddp_ds/infer.sh
+13
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swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/lora_ddp_ds/sft.sh
...es/pytorch/llm/scripts/qwen_audio_chat/lora_ddp_ds/sft.sh
+40
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swift-main/examples/pytorch/llm/scripts/qwen_vl/lora_ddp_ds/infer.sh
...examples/pytorch/llm/scripts/qwen_vl/lora_ddp_ds/infer.sh
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swift-main/examples/pytorch/llm/scripts/qwen_vl/lora_ddp_ds/sft.sh
...n/examples/pytorch/llm/scripts/qwen_vl/lora_ddp_ds/sft.sh
+40
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/full_mp/infer.sh
...xamples/pytorch/llm/scripts/qwen_vl_chat/full_mp/infer.sh
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/full_mp/sft.sh
.../examples/pytorch/llm/scripts/qwen_vl_chat/full_mp/sft.sh
+15
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/full_mp_ddp/infer.sh
...les/pytorch/llm/scripts/qwen_vl_chat/full_mp_ddp/infer.sh
+6
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/full_mp_ddp/sft.sh
...mples/pytorch/llm/scripts/qwen_vl_chat/full_mp_ddp/sft.sh
+16
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/lora/infer.sh
...n/examples/pytorch/llm/scripts/qwen_vl_chat/lora/infer.sh
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/lora/sft.sh
...ain/examples/pytorch/llm/scripts/qwen_vl_chat/lora/sft.sh
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/lora_ddp_ds/infer.sh
...les/pytorch/llm/scripts/qwen_vl_chat/lora_ddp_ds/infer.sh
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/lora_ddp_ds/sft.sh
...mples/pytorch/llm/scripts/qwen_vl_chat/lora_ddp_ds/sft.sh
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swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/qlora/infer.sh
.../examples/pytorch/llm/scripts/qwen_vl_chat/qlora/infer.sh
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swift-main/examples/pytorch/llm/scripts/qwen_7b_chat_int8/qlora_ddp_ds/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: 2 * A10
# 2 * 19GB GPU memory
nproc_per_node
=
2
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0,1
\
torchrun
\
--nproc_per_node
=
$nproc_per_node
\
--master_port
29500
\
llm_sft.py
\
--model_id_or_path
qwen/Qwen-7B-Chat-Int8
\
--model_revision
master
\
--sft_type
lora
\
--tuner_backend
peft
\
--template_type
AUTO
\
--dtype
fp16
\
--output_dir
output
\
--ddp_backend
nccl
\
--dataset
damo-agent-mini-zh
\
--train_dataset_sample
20000
\
--num_train_epochs
1
\
--max_length
4096
\
--check_dataset_strategy
warning
\
--lora_rank
8
\
--lora_alpha
32
\
--lora_dropout_p
0.05
\
--lora_target_modules
ALL
\
--gradient_checkpointing
true
\
--batch_size
1
\
--weight_decay
0.1
\
--learning_rate
1e-4
\
--gradient_accumulation_steps
$(
expr
16 /
$nproc_per_node
)
\
--max_grad_norm
0.5
\
--warmup_ratio
0.03
\
--eval_steps
100
\
--save_steps
100
\
--save_total_limit
2
\
--logging_steps
10
\
--use_flash_attn
false
\
--deepspeed
default-zero2
\
swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/full_mp/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: A100
CUDA_VISIBLE_DEVICES
=
0
\
swift infer
\
--ckpt_dir
"output/qwen-audio-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
true
\
swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/full_mp/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: 2 * A100
# 2 * 50GB GPU memory
CUDA_VISIBLE_DEVICES
=
0,1
\
swift sft
\
--model_type
qwen-audio-chat
\
--sft_type
full
\
--train_dataset_sample
-1
\
--eval_steps
100
\
--output_dir
output
\
--num_train_epochs
1
\
--max_length
2048
\
--learning_rate
1e-5
\
--use_flash_attn
true
\
--save_only_model
true
\
--dataset
aishell1-mini-zh
\
--lazy_tokenize
true
\
swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/full_mp_ddp/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: A100
CUDA_VISIBLE_DEVICES
=
0
\
swift infer
\
--ckpt_dir
"output/qwen-audio-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
true
\
swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/full_mp_ddp/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: 4 * A100
# 4 * 50GB GPU memory
NPROC_PER_NODE
=
2
\
CUDA_VISIBLE_DEVICES
=
0,1,2,3
\
swift sft
\
--model_type
qwen-audio-chat
\
--sft_type
full
\
--train_dataset_sample
-1
\
--eval_steps
100
\
--output_dir
output
\
--num_train_epochs
1
\
--max_length
2048
\
--learning_rate
1e-5
\
--use_flash_attn
true
\
--save_only_model
true
\
--dataset
aishell1-mini-zh
\
--lazy_tokenize
true
\
swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/lora/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: V100, A10, 3090
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0
\
python llm_infer.py
\
--ckpt_dir
"output/qwen-audio-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
false
\
--max_new_tokens
2048
\
--temperature
0.3
\
--top_p
0.7
\
--repetition_penalty
1.
\
--do_sample
true
\
--merge_lora
false
\
swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/lora/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: V100, A10, 3090
# 21GB GPU memory
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0
\
python llm_sft.py
\
--model_id_or_path
qwen/Qwen-Audio-Chat
\
--model_revision
master
\
--sft_type
lora
\
--tuner_backend
peft
\
--template_type
AUTO
\
--dtype
AUTO
\
--output_dir
output
\
--dataset
aishell1-mini-zh
\
--train_dataset_sample
-1
\
--num_train_epochs
1
\
--max_length
2048
\
--check_dataset_strategy
warning
\
--lora_rank
8
\
--lora_alpha
32
\
--lora_dropout_p
0.05
\
--lora_target_modules
DEFAULT
\
--gradient_checkpointing
true
\
--batch_size
1
\
--weight_decay
0.1
\
--learning_rate
1e-4
\
--gradient_accumulation_steps
16
\
--max_grad_norm
0.5
\
--warmup_ratio
0.03
\
--eval_steps
100
\
--save_steps
100
\
--save_total_limit
2
\
--logging_steps
10
\
--use_flash_attn
false
\
--lazy_tokenize
true
\
swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/lora_ddp_ds/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: A10
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0
\
python llm_infer.py
\
--ckpt_dir
"output/qwen-audio-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
false
\
--max_new_tokens
2048
\
--temperature
0.3
\
--top_p
0.7
\
--repetition_penalty
1.
\
--do_sample
true
\
--merge_lora
false
\
swift-main/examples/pytorch/llm/scripts/qwen_audio_chat/lora_ddp_ds/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: 2 * A10
# 2 * 21GB GPU memory
nproc_per_node
=
2
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0,1
\
torchrun
\
--nproc_per_node
=
$nproc_per_node
\
--master_port
29500
\
llm_sft.py
\
--model_type
qwen-audio-chat
\
--sft_type
lora
\
--tuner_backend
peft
\
--template_type
AUTO
\
--dtype
AUTO
\
--output_dir
output
\
--ddp_backend
nccl
\
--dataset
aishell1-mini-zh
\
--train_dataset_sample
-1
\
--num_train_epochs
1
\
--max_length
2048
\
--check_dataset_strategy
warning
\
--lora_rank
8
\
--lora_alpha
32
\
--lora_dropout_p
0.05
\
--lora_target_modules
DEFAULT
\
--gradient_checkpointing
true
\
--batch_size
1
\
--weight_decay
0.1
\
--learning_rate
1e-4
\
--gradient_accumulation_steps
$(
expr
16 /
$nproc_per_node
)
\
--max_grad_norm
0.5
\
--warmup_ratio
0.03
\
--eval_steps
100
\
--save_steps
100
\
--save_total_limit
2
\
--logging_steps
10
\
--use_flash_attn
false
\
--deepspeed
default-zero2
\
--lazy_tokenize
true
\
swift-main/examples/pytorch/llm/scripts/qwen_vl/lora_ddp_ds/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: A10
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0
\
python llm_infer.py
\
--ckpt_dir
"output/qwen-vl/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
false
\
--max_new_tokens
2048
\
--temperature
0.7
\
--top_p
0.7
\
--repetition_penalty
1.
\
--do_sample
true
\
--merge_lora
false
\
swift-main/examples/pytorch/llm/scripts/qwen_vl/lora_ddp_ds/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: 2 * A10
# 2 * 21GB GPU memory
nproc_per_node
=
2
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0,1
\
torchrun
\
--nproc_per_node
=
$nproc_per_node
\
--master_port
29500
\
llm_sft.py
\
--model_id_or_path
qwen/Qwen-VL
\
--model_revision
master
\
--sft_type
lora
\
--tuner_backend
peft
\
--template_type
default
\
--dtype
AUTO
\
--output_dir
output
\
--ddp_backend
nccl
\
--dataset
coco-en-mini
\
--train_dataset_sample
-1
\
--num_train_epochs
1
\
--max_length
2048
\
--check_dataset_strategy
warning
\
--lora_rank
8
\
--lora_alpha
32
\
--lora_dropout_p
0.05
\
--lora_target_modules
c_attn attn.c_proj
\
--gradient_checkpointing
true
\
--batch_size
1
\
--weight_decay
0.1
\
--learning_rate
1e-4
\
--gradient_accumulation_steps
$(
expr
16 /
$nproc_per_node
)
\
--max_grad_norm
0.5
\
--warmup_ratio
0.03
\
--eval_steps
100
\
--save_steps
100
\
--save_total_limit
2
\
--logging_steps
10
\
--use_flash_attn
false
\
--deepspeed
default-zero2
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/full_mp/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: A100
CUDA_VISIBLE_DEVICES
=
0
\
swift infer
\
--ckpt_dir
"output/qwen-vl-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
true
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/full_mp/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: 2 * A100
# 2 * 55GB GPU memory
CUDA_VISIBLE_DEVICES
=
0,1
\
swift sft
\
--model_type
qwen-vl-chat
\
--sft_type
full
\
--train_dataset_sample
-1
\
--eval_steps
100
\
--output_dir
output
\
--num_train_epochs
1
\
--max_length
2048
\
--learning_rate
1e-5
\
--use_flash_attn
true
\
--save_only_model
true
\
--dataset
coco-en-mini
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/full_mp_ddp/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: A100
CUDA_VISIBLE_DEVICES
=
0
\
swift infer
\
--ckpt_dir
"output/qwen-vl-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
true
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/full_mp_ddp/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: 4 * A100
# 4 * 55GB GPU memory
NPROC_PER_NODE
=
2
\
CUDA_VISIBLE_DEVICES
=
0,1,2,3
\
swift sft
\
--model_type
qwen-vl-chat
\
--sft_type
full
\
--train_dataset_sample
-1
\
--eval_steps
100
\
--output_dir
output
\
--num_train_epochs
1
\
--max_length
2048
\
--learning_rate
1e-5
\
--use_flash_attn
true
\
--save_only_model
true
\
--dataset
coco-en-mini
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/lora/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: V100, A10, 3090
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0
\
python llm_infer.py
\
--ckpt_dir
"output/qwen-vl-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
false
\
--max_new_tokens
2048
\
--temperature
0.7
\
--top_p
0.7
\
--repetition_penalty
1.
\
--do_sample
true
\
--merge_lora
false
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/lora/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: V100, A10, 3090
# 21GB GPU memory
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0
\
python llm_sft.py
\
--model_id_or_path
qwen/Qwen-VL-Chat
\
--model_revision
master
\
--sft_type
lora
\
--tuner_backend
peft
\
--template_type
AUTO
\
--dtype
AUTO
\
--output_dir
output
\
--dataset
coco-en-mini
\
--train_dataset_sample
-1
\
--num_train_epochs
1
\
--max_length
2048
\
--check_dataset_strategy
warning
\
--lora_rank
8
\
--lora_alpha
32
\
--lora_dropout_p
0.05
\
--lora_target_modules
DEFAULT
\
--gradient_checkpointing
true
\
--batch_size
1
\
--weight_decay
0.1
\
--learning_rate
1e-4
\
--gradient_accumulation_steps
16
\
--max_grad_norm
0.5
\
--warmup_ratio
0.03
\
--eval_steps
100
\
--save_steps
100
\
--save_total_limit
2
\
--logging_steps
10
\
--use_flash_attn
false
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/lora_ddp_ds/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: A10
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0
\
python llm_infer.py
\
--ckpt_dir
"output/qwen-vl-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
false
\
--max_new_tokens
2048
\
--temperature
0.7
\
--top_p
0.7
\
--repetition_penalty
1.
\
--do_sample
true
\
--merge_lora
false
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/lora_ddp_ds/sft.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: 2 * A10
# 2 * 21GB GPU memory
nproc_per_node
=
2
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0,1
\
torchrun
\
--nproc_per_node
=
$nproc_per_node
\
--master_port
29500
\
llm_sft.py
\
--model_id_or_path
qwen/Qwen-VL-Chat
\
--model_revision
master
\
--sft_type
lora
\
--tuner_backend
peft
\
--template_type
AUTO
\
--dtype
AUTO
\
--output_dir
output
\
--ddp_backend
nccl
\
--dataset
coco-en-mini
\
--train_dataset_sample
-1
\
--num_train_epochs
1
\
--max_length
2048
\
--check_dataset_strategy
warning
\
--lora_rank
8
\
--lora_alpha
32
\
--lora_dropout_p
0.05
\
--lora_target_modules
c_attn attn.c_proj
\
--gradient_checkpointing
true
\
--batch_size
1
\
--weight_decay
0.1
\
--learning_rate
1e-4
\
--gradient_accumulation_steps
$(
expr
16 /
$nproc_per_node
)
\
--max_grad_norm
0.5
\
--warmup_ratio
0.03
\
--eval_steps
100
\
--save_steps
100
\
--save_total_limit
2
\
--logging_steps
10
\
--use_flash_attn
false
\
--deepspeed
default-zero2
\
swift-main/examples/pytorch/llm/scripts/qwen_vl_chat/qlora/infer.sh
0 → 100644
View file @
1bfbcff0
# Experimental environment: A10
PYTHONPATH
=
../../..
\
CUDA_VISIBLE_DEVICES
=
0
\
python llm_infer.py
\
--ckpt_dir
"output/qwen-vl-chat/vx-xxx/checkpoint-xxx"
\
--load_dataset_config
true
\
--use_flash_attn
false
\
--max_new_tokens
2048
\
--temperature
0.7
\
--top_p
0.7
\
--repetition_penalty
1.
\
--do_sample
true
\
--merge_lora
false
\
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