mirror of
https://github.com/hiyouga/LLaMA-Factory.git
synced 2025-12-14 10:56:56 +08:00
@@ -1,7 +1,20 @@
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# coding=utf-8
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# Calculates the flops of pre-trained models.
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# Usage: python cal_flops.py --model_name_or_path path_to_model --batch_size 1 --seq_length 512
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# Inspired by: https://www.deepspeed.ai/tutorials/flops-profiler/
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# Copyright 2024 Microsoft Corporation and the LlamaFactory team.
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#
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# This code is inspired by Microsoft's DeepSpeed library.
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# https://www.deepspeed.ai/tutorials/flops-profiler/
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import fire
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import torch
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@@ -17,6 +30,10 @@ def calculate_flops(
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seq_length: int = 256,
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flash_attn: str = "auto",
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):
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r"""
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Calculates the flops of pre-trained models.
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Usage: python cal_flops.py --model_name_or_path path_to_model --batch_size 1 --seq_length 512
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"""
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with get_accelerator().device(0):
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chat_model = ChatModel(dict(model_name_or_path=model_name_or_path, template="empty", flash_attn=flash_attn))
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fake_input = torch.ones((batch_size, seq_length), dtype=torch.long, device=chat_model.model.device)
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@@ -1,7 +1,20 @@
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# coding=utf-8
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# Calculates the optimal learning rate for 7B/13B models using LLaMA's hyper-parameters.
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# Usage: python cal_lr.py --model_name_or_path path_to_model --dataset alpaca_en --cutoff_len 1024 --batch_size 16
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# Inspired by: https://github.com/imoneoi/openchat/blob/master/ochat/training_deepspeed/train.py
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# Copyright 2024 imoneoi and the LlamaFactory team.
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#
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# This code is inspired by imoneoi's OpenChat library.
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# https://github.com/imoneoi/openchat/blob/3.6.0/ochat/training_deepspeed/train.py
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import math
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from typing import Literal
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@@ -32,6 +45,10 @@ def calculate_lr(
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cutoff_len: int = 1024, # i.e. maximum input length during training
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is_mistral: bool = False, # mistral model uses a smaller learning rate,
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):
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r"""
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Calculates the optimal learning rate for 7B/13B models using LLaMA's hyper-parameters.
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Usage: python cal_lr.py --model_name_or_path path_to_model --dataset alpaca_en --cutoff_len 1024 --batch_size 16
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"""
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model_args, data_args, training_args, _, _ = get_train_args(
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dict(
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stage=stage,
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@@ -1,6 +1,17 @@
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# coding=utf-8
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# Calculates the ppl on the dataset of the pre-trained models.
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# Usage: python cal_ppl.py --model_name_or_path path_to_model --save_name ppl.json
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# Copyright 2024 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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from dataclasses import dataclass
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@@ -56,6 +67,10 @@ def cal_ppl(
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max_samples: Optional[int] = None,
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train_on_prompt: bool = False,
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):
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r"""
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Calculates the ppl on the dataset of the pre-trained models.
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Usage: python cal_ppl.py --model_name_or_path path_to_model --save_name ppl.json
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"""
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model_args, data_args, training_args, finetuning_args, _ = get_train_args(
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dict(
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stage=stage,
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@@ -1,6 +1,17 @@
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# coding=utf-8
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# Calculates the distribution of the input lengths in the dataset.
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# Usage: python length_cdf.py --model_name_or_path path_to_model --dataset alpaca_en --template default
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# Copyright 2024 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from collections import defaultdict
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@@ -19,6 +30,10 @@ def length_cdf(
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template: str = "default",
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interval: int = 1000,
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):
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r"""
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Calculates the distribution of the input lengths in the dataset.
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Usage: python length_cdf.py --model_name_or_path path_to_model --dataset alpaca_en --template default
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"""
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model_args, data_args, training_args, _, _ = get_train_args(
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dict(
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stage="sft",
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@@ -1,7 +1,20 @@
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# coding=utf-8
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# Performs block expansion for LLaMA, Mistral, Qwen1.5 or Yi models.
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# Usage: python llama_pro.py --model_name_or_path meta-llama/Llama-2-7b-hf --output_dir llama2_pro --num_expand 8
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# Inspired by: https://github.com/TencentARC/LLaMA-Pro/blob/main/scripts/block_expansion.py
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# Copyright 2024 Tencent Inc. and the LlamaFactory team.
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#
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# This code is inspired by Tencent's LLaMA-Pro library.
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# https://github.com/TencentARC/LLaMA-Pro/blob/main/scripts/block_expansion.py
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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import os
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@@ -37,6 +50,10 @@ def block_expansion(
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shard_size: Optional[str] = "2GB",
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save_safetensors: Optional[bool] = False,
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):
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r"""
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Performs block expansion for LLaMA, Mistral, Qwen1.5 or Yi models.
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Usage: python llama_pro.py --model_name_or_path meta-llama/Llama-2-7b-hf --output_dir llama2_pro --num_expand 8
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"""
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config: "PretrainedConfig" = AutoConfig.from_pretrained(model_name_or_path)
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num_layers = getattr(config, "num_hidden_layers")
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setattr(config, "num_hidden_layers", num_layers + num_expand)
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@@ -1,8 +1,17 @@
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# coding=utf-8
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# Converts the Baichuan2-7B model in the same format as LLaMA2-7B.
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# Usage: python llamafy_baichuan2.py --input_dir input --output_dir output
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# Inspired by: https://huggingface.co/fireballoon/baichuan-llama-7b/blob/main/convert_baichuan_to_llama.py
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# Converted model: https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied
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# Copyright 2024 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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import os
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@@ -79,6 +88,11 @@ def save_config(input_dir: str, output_dir: str):
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def llamafy_baichuan2(
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input_dir: str, output_dir: str, shard_size: Optional[str] = "2GB", save_safetensors: Optional[bool] = False
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):
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r"""
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Converts the Baichuan2-7B model in the same format as LLaMA2-7B.
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Usage: python llamafy_baichuan2.py --input_dir input --output_dir output
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Converted model: https://huggingface.co/hiyouga/Baichuan2-7B-Base-LLaMAfied
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"""
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try:
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os.makedirs(output_dir, exist_ok=False)
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except Exception as e:
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@@ -1,7 +1,17 @@
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# coding=utf-8
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# Converts the Qwen models in the same format as LLaMA2.
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# Usage: python llamafy_qwen.py --input_dir input --output_dir output
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# Converted model: https://huggingface.co/hiyouga/Qwen-14B-Chat-LLaMAfied
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# Copyright 2024 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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import os
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@@ -131,6 +141,11 @@ def save_config(input_dir: str, output_dir: str, torch_dtype: str):
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def llamafy_qwen(
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input_dir: str, output_dir: str, shard_size: Optional[str] = "2GB", save_safetensors: Optional[bool] = False
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):
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r"""
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Converts the Qwen models in the same format as LLaMA2.
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Usage: python llamafy_qwen.py --input_dir input --output_dir output
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Converted model: https://huggingface.co/hiyouga/Qwen-14B-Chat-LLaMAfied
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"""
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try:
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os.makedirs(output_dir, exist_ok=False)
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except Exception as e:
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@@ -1,7 +1,20 @@
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# coding=utf-8
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# Initializes LoRA weights with LoRA-fine-tuning-aware Quantization (LoftQ)
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# Usage: python loftq_init.py --model_name_or_path path_to_model --save_dir output_dir
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# Inspired by: https://github.com/huggingface/peft/blob/main/examples/loftq_finetuning/quantize_save_load.py
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# Copyright 2024 HuggingFace Inc. and the LlamaFactory team.
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#
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# This code is inspired by HuggingFace's PEFT library.
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# https://github.com/huggingface/peft/blob/v0.10.0/examples/loftq_finetuning/quantize_save_load.py
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
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# See the License for the specific language governing permissions and
|
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# limitations under the License.
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import os
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from typing import TYPE_CHECKING, Optional
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@@ -49,6 +62,10 @@ def quantize_loftq(
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lora_target: Optional[str] = "q_proj,v_proj",
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save_safetensors: Optional[bool] = False,
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):
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r"""
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Initializes LoRA weights with LoRA-fine-tuning-aware Quantization (LoftQ)
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Usage: python loftq_init.py --model_name_or_path path_to_model --save_dir output_dir
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"""
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tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(model_name_or_path, trust_remote_code=True, torch_dtype="auto")
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loftq_config = LoftQConfig(loftq_bits=loftq_bits, loftq_iter=loftq_iter)
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@@ -1,3 +1,18 @@
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# coding=utf-8
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# Copyright 2024 the LlamaFactory team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
|
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# You may obtain a copy of the License at
|
||||
#
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# http://www.apache.org/licenses/LICENSE-2.0
|
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#
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# 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.
|
||||
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import json
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import os
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from typing import Sequence
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Block a user