[misc] fix constants (#9008)

2025-09-01 18:52:50 +08:00 · 2025-08-23 23:04:30 +08:00 · 2025-08-23 23:04:30 +08:00 · 514d6d74fa
commit 514d6d74fa
parent 652e6e92da
8 changed files with 40 additions and 16 deletions
--- a/README.md
+++ b/README.md
@ -5,7 +5,7 @@
 [![GitHub contributors](https://img.shields.io/github/contributors/hiyouga/LLaMA-Factory?color=orange)](https://github.com/hiyouga/LLaMA-Factory/graphs/contributors)
 [![GitHub workflow](https://github.com/hiyouga/LLaMA-Factory/actions/workflows/tests.yml/badge.svg)](https://github.com/hiyouga/LLaMA-Factory/actions/workflows/tests.yml)
 [![PyPI](https://img.shields.io/pypi/v/llamafactory)](https://pypi.org/project/llamafactory/)
-[![Citation](https://img.shields.io/badge/citation-760-green)](https://scholar.google.com/scholar?cites=12620864006390196564)
+[![Citation](https://img.shields.io/badge/citation-818-green)](https://scholar.google.com/scholar?cites=12620864006390196564)
 [![Docker Pulls](https://img.shields.io/docker/pulls/hiyouga/llamafactory)](https://hub.docker.com/r/hiyouga/llamafactory/tags)

 [![Twitter](https://img.shields.io/twitter/follow/llamafactory_ai)](https://twitter.com/llamafactory_ai)
@ -124,12 +124,12 @@ Choose your path:

 [25/08/06] We supported fine-tuning the **[GPT-OSS](https://github.com/openai/gpt-oss)** models. See [PR #8826](https://github.com/hiyouga/LLaMA-Factory/pull/8826) to get started.

+<details><summary>Full Changelog</summary>
+
 [25/07/02] We supported fine-tuning the **[GLM-4.1V-9B-Thinking](https://github.com/THUDM/GLM-4.1V-Thinking)** model.

 [25/04/28] We supported fine-tuning the **[Qwen3](https://qwenlm.github.io/blog/qwen3/)** model family.

-<details><summary>Full Changelog</summary>
-
 [25/04/21] We supported the **[Muon](https://github.com/KellerJordan/Muon)** optimizer. See [examples](examples/README.md) for usage. Thank [@tianshijing](https://github.com/tianshijing)'s PR.

 [25/04/16] We supported fine-tuning the **[InternVL3](https://huggingface.co/OpenGVLab/InternVL3-8B)** model. See [PR #7258](https://github.com/hiyouga/LLaMA-Factory/pull/7258) to get started.
--- a/README_zh.md
+++ b/README_zh.md
@ -5,7 +5,7 @@
 [![GitHub contributors](https://img.shields.io/github/contributors/hiyouga/LLaMA-Factory?color=orange)](https://github.com/hiyouga/LLaMA-Factory/graphs/contributors)
 [![GitHub workflow](https://github.com/hiyouga/LLaMA-Factory/actions/workflows/tests.yml/badge.svg)](https://github.com/hiyouga/LLaMA-Factory/actions/workflows/tests.yml)
 [![PyPI](https://img.shields.io/pypi/v/llamafactory)](https://pypi.org/project/llamafactory/)
-[![Citation](https://img.shields.io/badge/citation-760-green)](https://scholar.google.com/scholar?cites=12620864006390196564)
+[![Citation](https://img.shields.io/badge/citation-818-green)](https://scholar.google.com/scholar?cites=12620864006390196564)
 [![Docker Pulls](https://img.shields.io/docker/pulls/hiyouga/llamafactory)](https://hub.docker.com/r/hiyouga/llamafactory/tags)

 [![Twitter](https://img.shields.io/twitter/follow/llamafactory_ai)](https://twitter.com/llamafactory_ai)
@ -87,7 +87,7 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc
 - **多种模型**：LLaMA、LLaVA、Mistral、Mixtral-MoE、Qwen、Qwen2-VL、DeepSeek、Yi、Gemma、ChatGLM、Phi 等等。
 - **集成方法**：（增量）预训练、（多模态）指令监督微调、奖励模型训练、PPO 训练、DPO 训练、KTO 训练、ORPO 训练等等。
 - **多种精度**：16 比特全参数微调、冻结微调、LoRA 微调和基于 AQLM/AWQ/GPTQ/LLM.int8/HQQ/EETQ 的 2/3/4/5/6/8 比特 QLoRA 微调。
- **先进算法**：[GaLore](https://github.com/jiaweizzhao/GaLore)、[BAdam](https://github.com/Ledzy/BAdam)、[APOLLO](https://github.com/zhuhanqing/APOLLO)、[Adam-mini](https://github.com/zyushun/Adam-mini)、[Muon](https://github.com/KellerJordan/Muon)、 [OFT](https://github.com/huggingface/peft/tree/main/src/peft/tuners/oft)、DoRA、LongLoRA、LLaMA Pro、Mixture-of-Depths、LoRA+、LoftQ 和 PiSSA。
+- **先进算法**：[GaLore](https://github.com/jiaweizzhao/GaLore)、[BAdam](https://github.com/Ledzy/BAdam)、[APOLLO](https://github.com/zhuhanqing/APOLLO)、[Adam-mini](https://github.com/zyushun/Adam-mini)、[Muon](https://github.com/KellerJordan/Muon)、[OFT](https://github.com/huggingface/peft/tree/main/src/peft/tuners/oft)、DoRA、LongLoRA、LLaMA Pro、Mixture-of-Depths、LoRA+、LoftQ 和 PiSSA。
 - **实用技巧**：[FlashAttention-2](https://github.com/Dao-AILab/flash-attention)、[Unsloth](https://github.com/unslothai/unsloth)、[Liger Kernel](https://github.com/linkedin/Liger-Kernel)、RoPE scaling、NEFTune 和 rsLoRA。
 - **广泛任务**：多轮对话、工具调用、图像理解、视觉定位、视频识别和语音理解等等。
 - **实验监控**：LlamaBoard、TensorBoard、Wandb、MLflow、[SwanLab](https://github.com/SwanHubX/SwanLab) 等等。
@ -126,12 +126,12 @@ https://github.com/user-attachments/assets/43b700c6-a178-41db-b1f8-8190a5d3fcfc

 [25/08/06] 我们支持了 **[GPT-OSS](https://github.com/openai/gpt-oss)** 模型的微调。查看 [PR #8826](https://github.com/hiyouga/LLaMA-Factory/pull/8826) 以使用。

+<details><summary>展开日志</summary>
+
 [25/07/02] 我们支持了 **[GLM-4.1V-9B-Thinking](https://github.com/THUDM/GLM-4.1V-Thinking)** 模型的微调。

 [25/04/28] 我们支持了 **[Qwen3](https://qwenlm.github.io/blog/qwen3/)** 系列模型的微调。

-<details><summary>展开日志</summary>
-
 [25/04/21] 我们支持了 **[Muon](https://github.com/KellerJordan/Muon)** 优化器。详细用法请参照 [examples](examples/README_zh.md)。感谢 [@tianshijing](https://github.com/tianshijing) 的 PR。

 [25/04/16] 我们支持了 **[InternVL3](https://huggingface.co/OpenGVLab/InternVL3-8B)** 模型的微调。查看 [PR #7258](https://github.com/hiyouga/LLaMA-Factory/pull/7258) 以使用。
--- a/assets/wechat.jpg
+++ b/assets/wechat.jpg
--- a/assets/wechat_npu.jpg
+++ b/assets/wechat_npu.jpg
--- a/src/llamafactory/data/formatter.py
+++ b/src/llamafactory/data/formatter.py
@ -98,7 +98,7 @@ class FunctionFormatter(StringFormatter):
    def apply(self, **kwargs) -> SLOTS:
        content: str = kwargs.pop("content")
        thought_words, thought = kwargs.pop("thought_words", None), None
-        if thought_words and len(thought_words)== 2:
+        if thought_words and len(thought_words) == 2:
            regex = re.compile(rf"{re.escape(thought_words[0])}(.*?){re.escape(thought_words[1])}", re.DOTALL)
            thought = re.search(regex, content)

--- a/src/llamafactory/data/template.py
+++ b/src/llamafactory/data/template.py
@ -1855,19 +1855,17 @@ register_template(
 )


-#copied from seed_coder
+# copied from seed_coder
 register_template(
    name="seed_oss",
    format_user=StringFormatter(
        slots=[{"bos_token"}, "user\n{{content}}", {"eos_token"}, {"bos_token"}, "assistant\n"]
    ),
    format_system=StringFormatter(slots=[{"bos_token"}, "system\n{{content}}", {"eos_token"}]),
-    format_function=FunctionFormatter(
-        slots=[{"bos_token"}, "\n{{content}}", {"eos_token"}], tool_format="seed_oss"
-    ),
+    format_function=FunctionFormatter(slots=[{"bos_token"}, "\n{{content}}", {"eos_token"}], tool_format="seed_oss"),
    format_tools=ToolFormatter(tool_format="seed_oss"),
    template_class=ReasoningTemplate,
-    thought_words=("<seed:think>", "</seed:think>")
+    thought_words=("<seed:think>", "</seed:think>"),
 )


--- a/src/llamafactory/data/tool_utils.py
+++ b/src/llamafactory/data/tool_utils.py
@ -355,6 +355,7 @@ class GLM4MOEToolUtils(QwenToolUtils):

        return "\n".join(function_texts)

+
 class SeedToolUtils(ToolUtils):
    r"""Seed tool using template."""

@ -387,8 +388,7 @@ class SeedToolUtils(ToolUtils):
    def tool_extractor(content: str) -> Union[str, list["FunctionCall"]]:
        results = []
        regex = re.compile(
-            r"<seed:tool_call>\s*<function=\s*([^\s<]+)\s*(.*?)\s*</function>\s*</seed:tool_call>",
-            re.DOTALL
+            r"<seed:tool_call>\s*<function=\s*([^\s<]+)\s*(.*?)\s*</function>\s*</seed:tool_call>", re.DOTALL
        )
        for func_name, params_block in re.findall(regex, content):
            args_dict = {}
@ -405,6 +405,7 @@ class SeedToolUtils(ToolUtils):

        return results

+
 TOOLS = {
    "default": DefaultToolUtils(),
    "glm4": GLM4ToolUtils(),
--- a/src/llamafactory/extras/constants.py
+++ b/src/llamafactory/extras/constants.py
@ -645,6 +645,7 @@ register_model_group(
    template="falcon",
 )

+
 register_model_group(
    models={
        "Falcon-H1-0.5B-Base": {
@ -1264,6 +1265,7 @@ register_model_group(
    multimodal=True,
 )

+
 register_model_group(
    models={
        "Intern-S1-mini": {
@ -1275,6 +1277,7 @@ register_model_group(
    multimodal=True,
 )

+
 register_model_group(
    models={
        "Jamba-v0.1": {
@ -3039,18 +3042,40 @@ register_model_group(
    models={
        "Seed-Coder-8B-Base": {
            DownloadSource.DEFAULT: "ByteDance-Seed/Seed-Coder-8B-Base",
+            DownloadSource.MODELSCOPE: "ByteDance-Seed/Seed-Coder-8B-Base",
        },
        "Seed-Coder-8B-Instruct": {
            DownloadSource.DEFAULT: "ByteDance-Seed/Seed-Coder-8B-Instruct",
+            DownloadSource.MODELSCOPE: "ByteDance-Seed/Seed-Coder-8B-Instruct",
        },
-        "Seed-Coder-8B-Instruct-Reasoning": {
+        "Seed-Coder-8B-Thinking": {
            DownloadSource.DEFAULT: "ByteDance-Seed/Seed-Coder-8B-Reasoning-bf16",
+            DownloadSource.MODELSCOPE: "ByteDance-Seed/Seed-Coder-8B-Reasoning-bf16",
        },
    },
    template="seed_coder",
 )


+register_model_group(
+    models={
+        "Seed-OSS-36B-Base": {
+            DownloadSource.DEFAULT: "ByteDance-Seed/Seed-OSS-36B-Base",
+            DownloadSource.MODELSCOPE: "ByteDance-Seed/Seed-OSS-36B-Base",
+        },
+        "Seed-OSS-36B-Base-woSyn": {
+            DownloadSource.DEFAULT: "ByteDance-Seed/Seed-OSS-36B-Base-woSyn",
+            DownloadSource.MODELSCOPE: "ByteDance-Seed/Seed-OSS-36B-Base-woSyn",
+        },
+        "Seed-OSS-36B-Instruct": {
+            DownloadSource.DEFAULT: "ByteDance-Seed/Seed-OSS-36B-Instruct",
+            DownloadSource.MODELSCOPE: "ByteDance-Seed/Seed-OSS-36B-Instruct",
+        },
+    },
+    template="seed_oss",
+)
+
+
 register_model_group(
    models={
        "Skywork-13B-Base": {