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add demo mode for web UI
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CODE_OF_CONDUCT.md
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128
CODE_OF_CONDUCT.md
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@ -0,0 +1,128 @@
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# Contributor Covenant Code of Conduct
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## Our Pledge
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We as members, contributors, and leaders pledge to make participation in our
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community a harassment-free experience for everyone, regardless of age, body
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size, visible or invisible disability, ethnicity, sex characteristics, gender
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identity and expression, level of experience, education, socio-economic status,
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nationality, personal appearance, race, religion, or sexual identity
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and orientation.
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We pledge to act and interact in ways that contribute to an open, welcoming,
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diverse, inclusive, and healthy community.
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## Our Standards
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Examples of behavior that contributes to a positive environment for our
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community include:
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* Demonstrating empathy and kindness toward other people
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* Being respectful of differing opinions, viewpoints, and experiences
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* Giving and gracefully accepting constructive feedback
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* Accepting responsibility and apologizing to those affected by our mistakes,
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and learning from the experience
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* Focusing on what is best not just for us as individuals, but for the
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overall community
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Examples of unacceptable behavior include:
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* The use of sexualized language or imagery, and sexual attention or
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advances of any kind
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* Trolling, insulting or derogatory comments, and personal or political attacks
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* Public or private harassment
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* Publishing others' private information, such as a physical or email
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address, without their explicit permission
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* Other conduct which could reasonably be considered inappropriate in a
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professional setting
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## Enforcement Responsibilities
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Community leaders are responsible for clarifying and enforcing our standards of
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acceptable behavior and will take appropriate and fair corrective action in
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response to any behavior that they deem inappropriate, threatening, offensive,
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or harmful.
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Community leaders have the right and responsibility to remove, edit, or reject
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comments, commits, code, wiki edits, issues, and other contributions that are
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not aligned to this Code of Conduct, and will communicate reasons for moderation
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decisions when appropriate.
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## Scope
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This Code of Conduct applies within all community spaces, and also applies when
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an individual is officially representing the community in public spaces.
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Examples of representing our community include using an official e-mail address,
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posting via an official social media account, or acting as an appointed
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representative at an online or offline event.
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## Enforcement
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Instances of abusive, harassing, or otherwise unacceptable behavior may be
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reported to the community leaders responsible for enforcement at
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`hoshihiyouga AT gmail DOT com`.
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All complaints will be reviewed and investigated promptly and fairly.
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All community leaders are obligated to respect the privacy and security of the
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reporter of any incident.
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## Enforcement Guidelines
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Community leaders will follow these Community Impact Guidelines in determining
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the consequences for any action they deem in violation of this Code of Conduct:
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### 1. Correction
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**Community Impact**: Use of inappropriate language or other behavior deemed
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unprofessional or unwelcome in the community.
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**Consequence**: A private, written warning from community leaders, providing
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clarity around the nature of the violation and an explanation of why the
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behavior was inappropriate. A public apology may be requested.
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### 2. Warning
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**Community Impact**: A violation through a single incident or series
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of actions.
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**Consequence**: A warning with consequences for continued behavior. No
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interaction with the people involved, including unsolicited interaction with
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those enforcing the Code of Conduct, for a specified period of time. This
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includes avoiding interactions in community spaces as well as external channels
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like social media. Violating these terms may lead to a temporary or
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permanent ban.
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### 3. Temporary Ban
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**Community Impact**: A serious violation of community standards, including
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sustained inappropriate behavior.
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**Consequence**: A temporary ban from any sort of interaction or public
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communication with the community for a specified period of time. No public or
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private interaction with the people involved, including unsolicited interaction
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with those enforcing the Code of Conduct, is allowed during this period.
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Violating these terms may lead to a permanent ban.
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### 4. Permanent Ban
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**Community Impact**: Demonstrating a pattern of violation of community
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standards, including sustained inappropriate behavior, harassment of an
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individual, or aggression toward or disparagement of classes of individuals.
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**Consequence**: A permanent ban from any sort of public interaction within
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the community.
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## Attribution
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This Code of Conduct is adapted from the [Contributor Covenant][homepage],
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version 2.0, available at
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https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
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Community Impact Guidelines were inspired by [Mozilla's code of conduct
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enforcement ladder](https://github.com/mozilla/diversity).
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[homepage]: https://www.contributor-covenant.org
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For answers to common questions about this code of conduct, see the FAQ at
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https://www.contributor-covenant.org/faq. Translations are available at
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https://www.contributor-covenant.org/translations.
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@ -14,7 +14,9 @@
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## LLaMA Board: A One-stop Web UI for Getting Started with LLaMA Factory
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## LLaMA Board: A One-stop Web UI for Getting Started with LLaMA Factory
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Launch **LLaMA Board** via `CUDA_VISIBLE_DEVICES=0 python src/train_web.py`. (multiple GPUs are not supported yet)
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Preview LLaMA Board at **[Hugging Face Space](https://huggingface.co/spaces/hiyouga/LLaMA-Board)**.
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Launch LLaMA Board via `CUDA_VISIBLE_DEVICES=0 python src/train_web.py`. (multiple GPUs are not supported yet)
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Here is an example of altering the self-cognition of an instruction-tuned language model within 10 minutes on a single GPU.
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Here is an example of altering the self-cognition of an instruction-tuned language model within 10 minutes on a single GPU.
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@ -14,7 +14,9 @@
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## LLaMA Board: 通过一站式网页界面快速上手 LLaMA Factory
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## LLaMA Board: 通过一站式网页界面快速上手 LLaMA Factory
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使用 `CUDA_VISIBLE_DEVICES=0 python src/train_web.py` 启动 **LLaMA Board**。(该界面目前仅支持单卡训练)
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通过 **[Hugging Face Space](https://huggingface.co/spaces/hiyouga/LLaMA-Board)** 预览 LLaMA Board。
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使用 `CUDA_VISIBLE_DEVICES=0 python src/train_web.py` 启动 LLaMA Board。(该界面目前仅支持单卡训练)
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下面是使用单张 GPU 在 10 分钟内更改对话式大型语言模型自我认知的示例。
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下面是使用单张 GPU 在 10 分钟内更改对话式大型语言模型自我认知的示例。
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@ -14,8 +14,14 @@ if TYPE_CHECKING:
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class WebChatModel(ChatModel):
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class WebChatModel(ChatModel):
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def __init__(self, manager: "Manager", lazy_init: Optional[bool] = True) -> None:
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def __init__(
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self,
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manager: "Manager",
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demo_mode: Optional[bool] = False,
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lazy_init: Optional[bool] = True
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) -> None:
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self.manager = manager
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self.manager = manager
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self.demo_mode = demo_mode
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self.model = None
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self.model = None
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self.tokenizer = None
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self.tokenizer = None
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self.generating_args = GeneratingArguments()
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self.generating_args = GeneratingArguments()
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@ -36,6 +42,8 @@ class WebChatModel(ChatModel):
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error = ALERTS["err_no_model"][lang]
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error = ALERTS["err_no_model"][lang]
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elif not get("top.model_path"):
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elif not get("top.model_path"):
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error = ALERTS["err_no_path"][lang]
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error = ALERTS["err_no_path"][lang]
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elif self.demo_mode:
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error = ALERTS["err_demo"][lang]
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if error:
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if error:
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gr.Warning(error)
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gr.Warning(error)
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@ -70,7 +70,7 @@ def get_module(model_name: str) -> str:
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def get_template(model_name: str) -> str:
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def get_template(model_name: str) -> str:
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if model_name.endswith("Chat") and get_prefix(model_name) in DEFAULT_TEMPLATE:
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if model_name and model_name.endswith("Chat") and get_prefix(model_name) in DEFAULT_TEMPLATE:
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return DEFAULT_TEMPLATE[get_prefix(model_name)]
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return DEFAULT_TEMPLATE[get_prefix(model_name)]
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return "default"
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return "default"
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@ -1,4 +1,11 @@
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CSS = r"""
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CSS = r"""
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.duplicate-button {
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margin: auto;
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color: white;
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background: black;
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border-radius: 100vh;
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}
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.modal-box {
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.modal-box {
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position: fixed !important;
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position: fixed !important;
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top: 50%;
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top: 50%;
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@ -12,11 +12,11 @@ from llmtuner.webui.utils import get_time
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class Engine:
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class Engine:
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def __init__(self, pure_chat: Optional[bool] = False) -> None:
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def __init__(self, demo_mode: Optional[bool] = False, pure_chat: Optional[bool] = False) -> None:
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self.pure_chat = pure_chat
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self.pure_chat = pure_chat
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self.manager: "Manager" = Manager()
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self.manager = Manager()
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self.runner: "Runner" = Runner(self.manager)
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self.runner = Runner(self.manager, demo_mode=demo_mode)
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self.chatter: "WebChatModel" = WebChatModel(manager=self.manager, lazy_init=(not pure_chat))
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self.chatter = WebChatModel(manager=self.manager, demo_mode=demo_mode, lazy_init=(not pure_chat))
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def _form_dict(self, resume_dict: Dict[str, Dict[str, Any]]):
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def _form_dict(self, resume_dict: Dict[str, Dict[str, Any]]):
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return {self.manager.get_elem_by_name(k): gr.update(**v) for k, v in resume_dict.items()}
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return {self.manager.get_elem_by_name(k): gr.update(**v) for k, v in resume_dict.items()}
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@ -1,4 +1,5 @@
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import gradio as gr
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import gradio as gr
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from typing import Optional
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from transformers.utils.versions import require_version
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from transformers.utils.versions import require_version
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from llmtuner.webui.components import (
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from llmtuner.webui.components import (
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@ -17,10 +18,20 @@ from llmtuner.webui.engine import Engine
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require_version("gradio>=3.38.0,<4.0.0", "To fix: pip install \"gradio>=3.38.0,<4.0.0\"")
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require_version("gradio>=3.38.0,<4.0.0", "To fix: pip install \"gradio>=3.38.0,<4.0.0\"")
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def create_ui() -> gr.Blocks:
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def create_ui(demo_mode: Optional[bool] = False) -> gr.Blocks:
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engine = Engine(pure_chat=False)
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engine = Engine(demo_mode=demo_mode, pure_chat=False)
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with gr.Blocks(title="LLaMA Board", css=CSS) as demo:
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with gr.Blocks(title="LLaMA Board", css=CSS) as demo:
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if demo_mode:
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gr.HTML(
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"<h1><center>LLaMA Board: A One-stop Web UI for Getting Started with LLaMA Factory</center></h1>"
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)
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gr.HTML(
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"<h3><center>Visit <a href=\"https://github.com/hiyouga/LLaMA-Factory\" target=\"_blank\">"
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"LLaMA Factory</a> for details.</center></h3>"
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)
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gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button")
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engine.manager.all_elems["top"] = create_top()
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engine.manager.all_elems["top"] = create_top()
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lang: "gr.Dropdown" = engine.manager.get_elem_by_name("top.lang")
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lang: "gr.Dropdown" = engine.manager.get_elem_by_name("top.lang")
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@ -33,8 +44,9 @@ def create_ui() -> gr.Blocks:
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with gr.Tab("Chat"):
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with gr.Tab("Chat"):
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engine.manager.all_elems["infer"] = create_infer_tab(engine)
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engine.manager.all_elems["infer"] = create_infer_tab(engine)
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with gr.Tab("Export"):
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if not demo_mode:
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engine.manager.all_elems["export"] = create_export_tab(engine)
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with gr.Tab("Export"):
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engine.manager.all_elems["export"] = create_export_tab(engine)
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demo.load(engine.resume, outputs=engine.manager.list_elems())
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demo.load(engine.resume, outputs=engine.manager.list_elems())
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lang.change(engine.change_lang, [lang], engine.manager.list_elems(), queue=False)
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lang.change(engine.change_lang, [lang], engine.manager.list_elems(), queue=False)
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@ -659,6 +659,10 @@ ALERTS = {
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"en": "Failed.",
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"en": "Failed.",
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"zh": "训练出错。"
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"zh": "训练出错。"
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},
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},
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"err_demo": {
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"en": "Training is unavailable in demo mode, duplicate the space to a private one first.",
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"zh": "展示模式不支持训练,请先复制到私人空间。"
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},
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"info_aborting": {
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"info_aborting": {
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"en": "Aborted, wait for terminating...",
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"en": "Aborted, wait for terminating...",
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"zh": "训练中断,正在等待线程结束……"
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"zh": "训练中断,正在等待线程结束……"
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@ -4,7 +4,7 @@ import logging
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import gradio as gr
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import gradio as gr
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from threading import Thread
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from threading import Thread
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from gradio.components import Component # cannot use TYPE_CHECKING here
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from gradio.components import Component # cannot use TYPE_CHECKING here
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from typing import TYPE_CHECKING, Any, Dict, Generator, Tuple
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from typing import TYPE_CHECKING, Any, Dict, Generator, Optional, Tuple
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import transformers
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import transformers
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from transformers.trainer import TRAINING_ARGS_NAME
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from transformers.trainer import TRAINING_ARGS_NAME
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@ -24,8 +24,9 @@ if TYPE_CHECKING:
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class Runner:
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class Runner:
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def __init__(self, manager: "Manager") -> None:
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def __init__(self, manager: "Manager", demo_mode: Optional[bool] = False) -> None:
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self.manager = manager
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self.manager = manager
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self.demo_mode = demo_mode
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""" Resume """
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""" Resume """
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self.thread: "Thread" = None
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self.thread: "Thread" = None
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self.do_train = True
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self.do_train = True
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@ -46,9 +47,8 @@ class Runner:
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def set_abort(self) -> None:
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def set_abort(self) -> None:
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self.aborted = True
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self.aborted = True
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self.running = False
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def _initialize(self, data: Dict[Component, Any], do_train: bool) -> str:
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def _initialize(self, data: Dict[Component, Any], do_train: bool, from_preview: bool) -> str:
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get = lambda name: data[self.manager.get_elem_by_name(name)]
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get = lambda name: data[self.manager.get_elem_by_name(name)]
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lang, model_name, model_path = get("top.lang"), get("top.model_name"), get("top.model_path")
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lang, model_name, model_path = get("top.lang"), get("top.model_name"), get("top.model_path")
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dataset = get("train.dataset") if do_train else get("eval.dataset")
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dataset = get("train.dataset") if do_train else get("eval.dataset")
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@ -65,6 +65,9 @@ class Runner:
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if len(dataset) == 0:
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if len(dataset) == 0:
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return ALERTS["err_no_dataset"][lang]
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return ALERTS["err_no_dataset"][lang]
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if self.demo_mode and (not from_preview):
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return ALERTS["err_demo"][lang]
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self.aborted = False
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self.aborted = False
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self.logger_handler.reset()
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self.logger_handler.reset()
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self.trainer_callback = LogCallback(self)
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self.trainer_callback = LogCallback(self)
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@ -196,7 +199,7 @@ class Runner:
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return args
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return args
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def _preview(self, data: Dict[Component, Any], do_train: bool) -> Generator[Tuple[str, Dict[str, Any]], None, None]:
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def _preview(self, data: Dict[Component, Any], do_train: bool) -> Generator[Tuple[str, Dict[str, Any]], None, None]:
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error = self._initialize(data, do_train)
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error = self._initialize(data, do_train, from_preview=True)
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if error:
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if error:
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gr.Warning(error)
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gr.Warning(error)
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yield error, gr.update(visible=False)
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yield error, gr.update(visible=False)
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@ -205,14 +208,13 @@ class Runner:
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yield gen_cmd(args), gr.update(visible=False)
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yield gen_cmd(args), gr.update(visible=False)
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|
|
||||||
def _launch(self, data: Dict[Component, Any], do_train: bool) -> Generator[Tuple[str, Dict[str, Any]], None, None]:
|
def _launch(self, data: Dict[Component, Any], do_train: bool) -> Generator[Tuple[str, Dict[str, Any]], None, None]:
|
||||||
error = self._initialize(data, do_train)
|
error = self._initialize(data, do_train, from_preview=False)
|
||||||
if error:
|
if error:
|
||||||
gr.Warning(error)
|
gr.Warning(error)
|
||||||
yield error, gr.update(visible=False)
|
yield error, gr.update(visible=False)
|
||||||
else:
|
else:
|
||||||
args = self._parse_train_args(data) if do_train else self._parse_eval_args(data)
|
args = self._parse_train_args(data) if do_train else self._parse_eval_args(data)
|
||||||
run_kwargs = dict(args=args, callbacks=[self.trainer_callback])
|
run_kwargs = dict(args=args, callbacks=[self.trainer_callback])
|
||||||
self.running = True
|
|
||||||
self.do_train, self.running_data = do_train, data
|
self.do_train, self.running_data = do_train, data
|
||||||
self.monitor_inputs = dict(lang=data[self.manager.get_elem_by_name("top.lang")], output_dir=args["output_dir"])
|
self.monitor_inputs = dict(lang=data[self.manager.get_elem_by_name("top.lang")], output_dir=args["output_dir"])
|
||||||
self.thread = Thread(target=run_exp, kwargs=run_kwargs)
|
self.thread = Thread(target=run_exp, kwargs=run_kwargs)
|
||||||
@ -232,6 +234,7 @@ class Runner:
|
|||||||
yield from self._launch(data, do_train=False)
|
yield from self._launch(data, do_train=False)
|
||||||
|
|
||||||
def monitor(self) -> Generator[Tuple[str, Dict[str, Any]], None, None]:
|
def monitor(self) -> Generator[Tuple[str, Dict[str, Any]], None, None]:
|
||||||
|
self.running = True
|
||||||
lang, output_dir = self.monitor_inputs["lang"], self.monitor_inputs["output_dir"]
|
lang, output_dir = self.monitor_inputs["lang"], self.monitor_inputs["output_dir"]
|
||||||
while self.thread.is_alive():
|
while self.thread.is_alive():
|
||||||
time.sleep(2)
|
time.sleep(2)
|
||||||
|
Loading…
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Reference in New Issue
Block a user