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support HQQ/EETQ #4113

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Former-commit-id: ad144c2265
This commit is contained in:
hiyouga
2024-06-27 00:29:42 +08:00
parent 6b2733ce12
commit d2d9fa4abb
16 changed files with 134 additions and 57 deletions
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10
src/llamafactory/webui/chatter.py
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@@ -23,7 +23,7 @@ from ..data import Role
from ..extras.constants import PEFT_METHODS
from ..extras.misc import torch_gc
from ..extras.packages import is_gradio_available
from .common import get_save_dir
from .common import QUANTIZATION_BITS, get_save_dir
from .locales import ALERTS
@@ -76,11 +76,17 @@ class WebChatModel(ChatModel):
yield error
return
if get("top.quantization_bit") in QUANTIZATION_BITS:
quantization_bit = int(get("top.quantization_bit"))
else:
quantization_bit = None
yield ALERTS["info_loading"][lang]
args = dict(
model_name_or_path=model_path,
finetuning_type=finetuning_type,
quantization_bit=int(get("top.quantization_bit")) if get("top.quantization_bit") in ["8", "4"] else None,
quantization_bit=quantization_bit,
quantization_method=get("top.quantization_method"),
template=get("top.template"),
flash_attn="fa2" if get("top.booster") == "flashattn2" else "auto",
use_unsloth=(get("top.booster") == "unsloth"),

2
src/llamafactory/webui/common.py
View File

@@ -47,6 +47,8 @@ DEFAULT_CONFIG_DIR = "config"
DEFAULT_DATA_DIR = "data"
DEFAULT_SAVE_DIR = "saves"
USER_CONFIG = "user_config.yaml"
QUANTIZATION_BITS = ["8", "6", "5", "4", "3", "2", "1"]
GPTQ_BITS = ["8", "4", "3", "2"]
def get_save_dir(*paths: str) -> os.PathLike:

5
src/llamafactory/webui/components/export.py
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@@ -18,7 +18,7 @@ from ...extras.constants import PEFT_METHODS
from ...extras.misc import torch_gc
from ...extras.packages import is_gradio_available
from ...train.tuner import export_model
from ..common import get_save_dir
from ..common import GPTQ_BITS, get_save_dir
from ..locales import ALERTS
@@ -32,9 +32,6 @@ if TYPE_CHECKING:
from ..engine import Engine
GPTQ_BITS = ["8", "4", "3", "2"]
def can_quantize(checkpoint_path: Union[str, List[str]]) -> "gr.Dropdown":
if isinstance(checkpoint_path, list) and len(checkpoint_path) != 0:
return gr.Dropdown(value="none", interactive=False)

13
src/llamafactory/webui/components/top.py
View File

@@ -18,7 +18,7 @@ from ...data import TEMPLATES
from ...extras.constants import METHODS, SUPPORTED_MODELS
from ...extras.packages import is_gradio_available
from ..common import get_model_info, list_checkpoints, save_config
from ..utils import can_quantize
from ..utils import can_quantize, can_quantize_to
if is_gradio_available():
@@ -43,10 +43,11 @@ def create_top() -> Dict[str, "Component"]:
with gr.Accordion(open=False) as advanced_tab:
with gr.Row():
quantization_bit = gr.Dropdown(choices=["none", "8", "4"], value="none", scale=2)
template = gr.Dropdown(choices=list(TEMPLATES.keys()), value="default", scale=2)
rope_scaling = gr.Radio(choices=["none", "linear", "dynamic"], value="none", scale=3)
booster = gr.Radio(choices=["none", "flashattn2", "unsloth"], value="none", scale=3)
quantization_bit = gr.Dropdown(choices=["none", "8", "4"], value="none", scale=1)
quantization_method = gr.Dropdown(choices=["bitsandbytes", "hqq", "eetq"], value="bitsandbytes", scale=1)
template = gr.Dropdown(choices=list(TEMPLATES.keys()), value="default", scale=1)
rope_scaling = gr.Radio(choices=["none", "linear", "dynamic"], value="none", scale=2)
booster = gr.Radio(choices=["auto", "flashattn2", "unsloth"], value="auto", scale=2)
visual_inputs = gr.Checkbox(scale=1)
model_name.change(get_model_info, [model_name], [model_path, template, visual_inputs], queue=False).then(
@@ -58,6 +59,7 @@ def create_top() -> Dict[str, "Component"]:
list_checkpoints, [model_name, finetuning_type], [checkpoint_path], queue=False
)
checkpoint_path.focus(list_checkpoints, [model_name, finetuning_type], [checkpoint_path], queue=False)
quantization_method.change(can_quantize_to, [quantization_method], [quantization_bit], queue=False)
return dict(
lang=lang,
@@ -67,6 +69,7 @@ def create_top() -> Dict[str, "Component"]:
checkpoint_path=checkpoint_path,
advanced_tab=advanced_tab,
quantization_bit=quantization_bit,
quantization_method=quantization_method,
template=template,
rope_scaling=rope_scaling,
booster=booster,

20
src/llamafactory/webui/locales.py
View File

@@ -85,15 +85,29 @@ LOCALES = {
"quantization_bit": {
"en": {
"label": "Quantization bit",
"info": "Enable 4/8-bit model quantization (QLoRA).",
"info": "Enable quantization (QLoRA).",
},
"ru": {
"label": "Уровень квантования",
"info": "Включить 4/8-битное квантование модели (QLoRA).",
"info": "Включить квантование (QLoRA).",
},
"zh": {
"label": "量化等级",
"info": "启用 4/8 比特模型量化（QLoRA）。",
"info": "启用量化（QLoRA）。",
},
},
"quantization_method": {
"en": {
"label": "Quantization method",
"info": "Quantization algorithm to use.",
},
"ru": {
"label": "Метод квантования",
"info": "Алгоритм квантования, который следует использовать.",
},
"zh": {
"label": "量化方法",
"info": "使用的量化算法。",
},
},
"template": {

1
src/llamafactory/webui/manager.py
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@@ -71,6 +71,7 @@ class Manager:
self._id_to_elem["top.finetuning_type"],
self._id_to_elem["top.checkpoint_path"],
self._id_to_elem["top.quantization_bit"],
self._id_to_elem["top.quantization_method"],
self._id_to_elem["top.template"],
self._id_to_elem["top.rope_scaling"],
self._id_to_elem["top.booster"],

18
src/llamafactory/webui/runner.py
View File

@@ -22,7 +22,7 @@ from transformers.trainer import TRAINING_ARGS_NAME
from ..extras.constants import LLAMABOARD_CONFIG, PEFT_METHODS, TRAINING_STAGES
from ..extras.misc import is_gpu_or_npu_available, torch_gc
from ..extras.packages import is_gradio_available
from .common import DEFAULT_CACHE_DIR, DEFAULT_CONFIG_DIR, get_save_dir, load_config
from .common import DEFAULT_CACHE_DIR, DEFAULT_CONFIG_DIR, QUANTIZATION_BITS, get_save_dir, load_config
from .locales import ALERTS, LOCALES
from .utils import abort_process, gen_cmd, get_eval_results, get_trainer_info, load_args, save_args, save_cmd
@@ -104,6 +104,11 @@ class Runner:
model_name, finetuning_type = get("top.model_name"), get("top.finetuning_type")
user_config = load_config()
if get("top.quantization_bit") in QUANTIZATION_BITS:
quantization_bit = int(get("top.quantization_bit"))
else:
quantization_bit = None
args = dict(
stage=TRAINING_STAGES[get("train.training_stage")],
do_train=True,
@@ -111,7 +116,8 @@ class Runner:
cache_dir=user_config.get("cache_dir", None),
preprocessing_num_workers=16,
finetuning_type=finetuning_type,
quantization_bit=int(get("top.quantization_bit")) if get("top.quantization_bit") in ["8", "4"] else None,
quantization_bit=quantization_bit,
quantization_method=get("top.quantization_method"),
template=get("top.template"),
rope_scaling=get("top.rope_scaling") if get("top.rope_scaling") in ["linear", "dynamic"] else None,
flash_attn="fa2" if get("top.booster") == "flashattn2" else "auto",
@@ -234,13 +240,19 @@ class Runner:
model_name, finetuning_type = get("top.model_name"), get("top.finetuning_type")
user_config = load_config()
if get("top.quantization_bit") in QUANTIZATION_BITS:
quantization_bit = int(get("top.quantization_bit"))
else:
quantization_bit = None
args = dict(
stage="sft",
model_name_or_path=get("top.model_path"),
cache_dir=user_config.get("cache_dir", None),
preprocessing_num_workers=16,
finetuning_type=finetuning_type,
quantization_bit=int(get("top.quantization_bit")) if get("top.quantization_bit") in ["8", "4"] else None,
quantization_bit=quantization_bit,
quantization_method=get("top.quantization_method"),
template=get("top.template"),
rope_scaling=get("top.rope_scaling") if get("top.rope_scaling") in ["linear", "dynamic"] else None,
flash_attn="fa2" if get("top.booster") == "flashattn2" else "auto",

13
src/llamafactory/webui/utils.py
View File

@@ -25,6 +25,7 @@ from yaml import safe_dump, safe_load
from ..extras.constants import PEFT_METHODS, RUNNING_LOG, TRAINER_LOG, TRAINING_ARGS, TRAINING_STAGES
from ..extras.packages import is_gradio_available, is_matplotlib_available
from ..extras.ploting import gen_loss_plot
from ..model import QuantizationMethod
from .common import DEFAULT_CACHE_DIR, DEFAULT_CONFIG_DIR, get_save_dir
from .locales import ALERTS
@@ -55,6 +56,18 @@ def can_quantize(finetuning_type: str) -> "gr.Dropdown":
return gr.Dropdown(interactive=True)
def can_quantize_to(quantization_method: str) -> "gr.Dropdown":
r"""
Returns the available quantization bits.
"""
if quantization_method == QuantizationMethod.BITS_AND_BYTES.value:
return gr.Dropdown(choices=["none", "8", "4"])
elif quantization_method == QuantizationMethod.HQQ.value:
return gr.Dropdown(choices=["none", "8", "6", "5", "4", "3", "2", "1"])
elif quantization_method == QuantizationMethod.EETQ.value:
return gr.Dropdown(choices=["none", "8"])
def change_stage(training_stage: str = list(TRAINING_STAGES.keys())[0]) -> Tuple[List[str], bool]:
r"""
Modifys states after changing the training stage.