add license

Former-commit-id: 69cfc98d7c81756a5ab6bf962240e393e449fef0
This commit is contained in:
hiyouga
2024-06-15 17:54:33 +08:00
parent 8b523554d6
commit acfae2e677
122 changed files with 1848 additions and 32 deletions

View File

@@ -1,7 +1,20 @@
# coding=utf-8
# Calculates the flops of pre-trained models.
# Usage: python cal_flops.py --model_name_or_path path_to_model --batch_size 1 --seq_length 512
# Inspired by: https://www.deepspeed.ai/tutorials/flops-profiler/
# Copyright 2024 Microsoft Corporation and the LlamaFactory team.
#
# This code is inspired by Microsoft's DeepSpeed library.
# https://www.deepspeed.ai/tutorials/flops-profiler/
#
# 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.
import fire
import torch
@@ -17,6 +30,10 @@ def calculate_flops(
seq_length: int = 256,
flash_attn: str = "auto",
):
r"""
Calculates the flops of pre-trained models.
Usage: python cal_flops.py --model_name_or_path path_to_model --batch_size 1 --seq_length 512
"""
with get_accelerator().device(0):
chat_model = ChatModel(dict(model_name_or_path=model_name_or_path, template="empty", flash_attn=flash_attn))
fake_input = torch.ones((batch_size, seq_length), dtype=torch.long, device=chat_model.model.device)

View File

@@ -1,7 +1,20 @@
# coding=utf-8
# Calculates the optimal learning rate for 7B/13B models using LLaMA's hyper-parameters.
# Usage: python cal_lr.py --model_name_or_path path_to_model --dataset alpaca_en --cutoff_len 1024 --batch_size 16
# Inspired by: https://github.com/imoneoi/openchat/blob/master/ochat/training_deepspeed/train.py
# Copyright 2024 imoneoi and the LlamaFactory team.
#
# This code is inspired by imoneoi's OpenChat library.
# https://github.com/imoneoi/openchat/blob/3.6.0/ochat/training_deepspeed/train.py
#
# 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.
import math
from typing import Literal
@@ -32,6 +45,10 @@ def calculate_lr(
cutoff_len: int = 1024, # i.e. maximum input length during training
is_mistral: bool = False, # mistral model uses a smaller learning rate,
):
r"""
Calculates the optimal learning rate for 7B/13B models using LLaMA's hyper-parameters.
Usage: python cal_lr.py --model_name_or_path path_to_model --dataset alpaca_en --cutoff_len 1024 --batch_size 16
"""
model_args, data_args, training_args, _, _ = get_train_args(
dict(
stage=stage,

View File

@@ -1,6 +1,17 @@
# coding=utf-8
# Calculates the ppl on the dataset of the pre-trained models.
# Usage: python cal_ppl.py --model_name_or_path path_to_model --save_name ppl.json
# Copyright 2024 the LlamaFactory team.
#
# 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.
import json
from dataclasses import dataclass
@@ -56,6 +67,10 @@ def cal_ppl(
max_samples: Optional[int] = None,
train_on_prompt: bool = False,
):
r"""
Calculates the ppl on the dataset of the pre-trained models.
Usage: python cal_ppl.py --model_name_or_path path_to_model --save_name ppl.json
"""
model_args, data_args, training_args, finetuning_args, _ = get_train_args(
dict(
stage=stage,

View File

@@ -1,6 +1,17 @@
# coding=utf-8
# Calculates the distribution of the input lengths in the dataset.
# Usage: python length_cdf.py --model_name_or_path path_to_model --dataset alpaca_en --template default
# Copyright 2024 the LlamaFactory team.
#
# 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 collections import defaultdict
@@ -19,6 +30,10 @@ def length_cdf(
template: str = "default",
interval: int = 1000,
):
r"""
Calculates the distribution of the input lengths in the dataset.
Usage: python length_cdf.py --model_name_or_path path_to_model --dataset alpaca_en --template default
"""
model_args, data_args, training_args, _, _ = get_train_args(
dict(
stage="sft",

View File

@@ -1,7 +1,20 @@
# coding=utf-8
# Performs block expansion for LLaMA, Mistral, Qwen1.5 or Yi models.
# Usage: python llama_pro.py --model_name_or_path meta-llama/Llama-2-7b-hf --output_dir llama2_pro --num_expand 8
# Inspired by: https://github.com/TencentARC/LLaMA-Pro/blob/main/scripts/block_expansion.py
# Copyright 2024 Tencent Inc. and the LlamaFactory team.
#
# This code is inspired by Tencent's LLaMA-Pro library.
# https://github.com/TencentARC/LLaMA-Pro/blob/main/scripts/block_expansion.py
#
# 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.
import json
import os
@@ -37,6 +50,10 @@ def block_expansion(
shard_size: Optional[str] = "2GB",
save_safetensors: Optional[bool] = False,
):
r"""
Performs block expansion for LLaMA, Mistral, Qwen1.5 or Yi models.
Usage: python llama_pro.py --model_name_or_path meta-llama/Llama-2-7b-hf --output_dir llama2_pro --num_expand 8
"""
config: "PretrainedConfig" = AutoConfig.from_pretrained(model_name_or_path)
num_layers = getattr(config, "num_hidden_layers")
setattr(config, "num_hidden_layers", num_layers + num_expand)

View File

@@ -1,8 +1,17 @@
# coding=utf-8
# Converts the Baichuan2-7B model in the same format as LLaMA2-7B.
# Usage: python llamafy_baichuan2.py --input_dir input --output_dir output
# Inspired by: https://huggingface.co/fireballoon/baichuan-llama-7b/blob/main/convert_baichuan_to_llama.py
# Converted model: https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied
# Copyright 2024 the LlamaFactory team.
#
# 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.
import json
import os
@@ -79,6 +88,11 @@ def save_config(input_dir: str, output_dir: str):
def llamafy_baichuan2(
input_dir: str, output_dir: str, shard_size: Optional[str] = "2GB", save_safetensors: Optional[bool] = False
):
r"""
Converts the Baichuan2-7B model in the same format as LLaMA2-7B.
Usage: python llamafy_baichuan2.py --input_dir input --output_dir output
Converted model: https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied
"""
try:
os.makedirs(output_dir, exist_ok=False)
except Exception as e:

View File

@@ -1,7 +1,17 @@
# coding=utf-8
# Converts the Qwen models in the same format as LLaMA2.
# Usage: python llamafy_qwen.py --input_dir input --output_dir output
# Converted model: https://huggingface.co/hiyouga/Qwen-14B-Chat-LLaMAfied
# Copyright 2024 the LlamaFactory team.
#
# 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.
import json
import os
@@ -131,6 +141,11 @@ def save_config(input_dir: str, output_dir: str, torch_dtype: str):
def llamafy_qwen(
input_dir: str, output_dir: str, shard_size: Optional[str] = "2GB", save_safetensors: Optional[bool] = False
):
r"""
Converts the Qwen models in the same format as LLaMA2.
Usage: python llamafy_qwen.py --input_dir input --output_dir output
Converted model: https://huggingface.co/hiyouga/Qwen-14B-Chat-LLaMAfied
"""
try:
os.makedirs(output_dir, exist_ok=False)
except Exception as e:

View File

@@ -1,7 +1,20 @@
# coding=utf-8
# Initializes LoRA weights with LoRA-fine-tuning-aware Quantization (LoftQ)
# Usage: python loftq_init.py --model_name_or_path path_to_model --save_dir output_dir
# Inspired by: https://github.com/huggingface/peft/blob/main/examples/loftq_finetuning/quantize_save_load.py
# Copyright 2024 HuggingFace Inc. and the LlamaFactory team.
#
# This code is inspired by HuggingFace's PEFT library.
# https://github.com/huggingface/peft/blob/v0.10.0/examples/loftq_finetuning/quantize_save_load.py
#
# 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.
import os
from typing import TYPE_CHECKING, Optional
@@ -49,6 +62,10 @@ def quantize_loftq(
lora_target: Optional[str] = "q_proj,v_proj",
save_safetensors: Optional[bool] = False,
):
r"""
Initializes LoRA weights with LoRA-fine-tuning-aware Quantization (LoftQ)
Usage: python loftq_init.py --model_name_or_path path_to_model --save_dir output_dir
"""
tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_name_or_path, trust_remote_code=True, torch_dtype="auto")
loftq_config = LoftQConfig(loftq_bits=loftq_bits, loftq_iter=loftq_iter)

View File

@@ -1,3 +1,18 @@
# coding=utf-8
# Copyright 2024 the LlamaFactory team.
#
# 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.
import json
import os
from typing import Sequence