update readme

.readthedocs.yaml

@@ -0,0 +1,19 @@
+# Read the Docs configuration file
+# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
+
+version: 2
+
+build:
+  os: ubuntu-22.04
+  tools:
+    python: "3.8"
+
+sphinx:
+  configuration: docs/source/conf.py
+
+formats:
+  - pdf
+
+python:
+  install:
+  - requirements: docs/requirements-docs.txt

README.md

@@ -330,7 +330,7 @@ cd LLaMA-Factory
 pip install -e .[torch,metrics]
 ```
 
-Extra dependencies available: torch, metrics, deepspeed, bitsandbytes, vllm, galore, badam, gptq, awq, aqlm, qwen, modelscope, quality
+Extra dependencies available: torch, torch_npu, metrics, deepspeed, bitsandbytes, vllm, galore, badam, gptq, awq, aqlm, qwen, modelscope, quality
 
 > [!TIP]
 > Use `pip install --no-deps -e .` to resolve package conflicts.
@@ -351,31 +351,27 @@ To enable FlashAttention-2 on the Windows platform, you need to install the prec
 
 Join [NPU user group](assets/wechat_npu.jpg).
 
-Use `pip install -e .[torch_npu]` to install LLaMA-Factory with **[torch-npu](https://gitee.com/ascend/pytorch)** library.
+To install LLaMA Factory on Ascend NPU devices, please specify extra dependencies: `pip install -e .[torch_npu,metrics]`. Additionally, you need to install the **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**. Please follow the [installation tutorial](https://www.hiascend.com/document/detail/en/CANNCommunityEdition/600alphaX/softwareinstall/instg/atlasdeploy_03_0031.html) or use the following commands:
-
-To utilize Ascend NPU devices for (distributed) training and inference, you need to install the **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**. You can follow chapter **[install CANN](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/80RC2alpha002/quickstart/quickstart/quickstart_18_0004.html)** in the installation tutorial to install CANN Toolkit and the kernels, or use the fast installation as following:
 
 ```bash
-# replace the url according to your choice
+# replace the url according to your CANN version and devices
 # install CANN Toolkit
 wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/Milan-ASL/Milan-ASL%20V100R001C17SPC701/Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run
-chmod +x Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run
+bash Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run --install
-./Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run --install
 
 # install CANN Kernels
 wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/Milan-ASL/Milan-ASL%20V100R001C17SPC701/Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run
-chmod +x Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run
+bash Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run --install
-./Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run --install
 
 # set env variables
 source /usr/local/Ascend/ascend-toolkit/set_env.sh
 ```
 
 | Requirement  | Minimum | Recommend   |
-| ------------ | ------- | --------- |
+| ------------ | ------- | ----------- |
 | CANN         | 8.0.RC1 | 8.0.RC1     |
-| torch        | 2.2.0   | 2.2.0     |
+| torch        | 2.1.0   | 2.1.0       |
-| torch-npu    | 2.2.0   | 2.2.0     |
+| torch-npu    | 2.1.0   | 2.1.0.post3 |
 | deepspeed    | 0.13.2  | 0.13.2      |
 
 Docker image:

README_zh.md

@@ -330,7 +330,7 @@ cd LLaMA-Factory
 pip install -e .[torch,metrics]
 ```
 
-可选的额外依赖项：torch、metrics、deepspeed、bitsandbytes、vllm、galore、badam、gptq、awq、aqlm、qwen、modelscope、quality
+可选的额外依赖项：torch、torch_npu、metrics、deepspeed、bitsandbytes、vllm、galore、badam、gptq、awq、aqlm、qwen、modelscope、quality
 
 > [!TIP]
 > 遇到包冲突时，可使用 `pip install --no-deps -e .` 解决。
@@ -351,31 +351,27 @@ pip install https://github.com/jllllll/bitsandbytes-windows-webui/releases/downl
 
 加入 [NPU 用户群](assets/wechat_npu.jpg)。
 
-使用 `pip install -e .[torch_npu]` 来安装带有 **[torch-npu](https://gitee.com/ascend/pytorch)** 的 LLaMA-Factory。
+在昇腾 NPU 设备上安装 LLaMA Factory 时，需要指定额外依赖项，使用 `pip install -e .[torch_npu,metrics]` 命令安装。此外，还需要安装 **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**，安装方法请参考[安装教程](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/80RC2alpha002/quickstart/quickstart/quickstart_18_0004.html)或使用以下命令：
-
-如果使用昇腾 NPU 设备进行（分布式）训练或推理，需要安装 **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**。可以参考安装教程中的**[安装 CANN](https://www.hiascend.com/document/detail/zh/CANNCommunityEdition/80RC2alpha002/quickstart/quickstart/quickstart_18_0004.html)**章节来进行安装，或使用以下快速安装指令：
 
 ```bash
-# 请替换 URL 为你需要的 CANN 版本对应的 URL
+# 请替换 URL 为 CANN 版本和设备型号对应的 URL
 # 安装 CANN Toolkit
 wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/Milan-ASL/Milan-ASL%20V100R001C17SPC701/Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run
-chmod +x Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run
+bash Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run --install
-./Ascend-cann-toolkit_8.0.RC1.alpha001_linux-"$(uname -i)".run --install
 
 # 安装 CANN Kernels
 wget https://ascend-repo.obs.cn-east-2.myhuaweicloud.com/Milan-ASL/Milan-ASL%20V100R001C17SPC701/Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run
-chmod +x Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run
+bash Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run --install
-./Ascend-cann-kernels-910b_8.0.RC1.alpha001_linux.run --install
 
 # 设置环境变量
 source /usr/local/Ascend/ascend-toolkit/set_env.sh
 ```
 
 | 依赖项       | 至少     | 推荐        |
-| ------------ | ------- | --------- |
+| ------------ | ------- | ----------- |
 | CANN         | 8.0.RC1 | 8.0.RC1     |
-| torch        | 2.2.0   | 2.2.0     |
+| torch        | 2.1.0   | 2.1.0       |
-| torch-npu    | 2.2.0   | 2.2.0     |
+| torch-npu    | 2.1.0   | 2.1.0.post3 |
 | deepspeed    | 0.13.2  | 0.13.2      |
 
 Docker 镜像：
@@ -383,7 +379,7 @@ Docker 镜像：
 - 32GB：[下载地址](http://mirrors.cn-central-221.ovaijisuan.com/detail/130.html)
 - 64GB：[下载地址](http://mirrors.cn-central-221.ovaijisuan.com/detail/131.html)
 
-请记得使用 `ASCEND_RT_VISIBLE_DEVICES` 而非 `CUDA_VISIBLE_DEVICES` 来指定您使用的设备。
+请使用 `ASCEND_RT_VISIBLE_DEVICES` 而非 `CUDA_VISIBLE_DEVICES` 来指定运算设备。
 
 如果遇到无法正常推理的情况，请尝试设置 `do_sample: false`。
 

examples/accelerate/fsdp_config.yaml

@@ -5,16 +5,16 @@ downcast_bf16: 'no'
 fsdp_config:
   fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
   fsdp_backward_prefetch: BACKWARD_PRE
-  fsdp_cpu_ram_efficient_loading: true
   fsdp_forward_prefetch: false
-  fsdp_offload_params: true
+  fsdp_cpu_ram_efficient_loading: true
+  fsdp_offload_params: true # offload may affect training speed
   fsdp_sharding_strategy: FULL_SHARD
   fsdp_state_dict_type: FULL_STATE_DICT
   fsdp_sync_module_states: true
-  fsdp_use_orig_params: false
+  fsdp_use_orig_params: true
 machine_rank: 0
 main_training_function: main
-mixed_precision: fp16
+mixed_precision: fp16 # or bf16
 num_machines: 1 # the number of nodes
 num_processes: 2 # the number of GPUs in all nodes
 rdzv_backend: static

setup.py

@@ -21,6 +21,7 @@ def get_requires():
 
 extra_require = {
     "torch": ["torch>=1.13.1"],
+    "torch_npu": ["torch==2.1.0", "torch-npu==2.1.0.post3", "decorator"],
     "metrics": ["nltk", "jieba", "rouge-chinese"],
     "deepspeed": ["deepspeed>=0.10.0,<=0.14.0"],
     "bitsandbytes": ["bitsandbytes>=0.39.0"],
@@ -33,7 +34,6 @@ extra_require = {
     "qwen": ["tiktoken", "transformers_stream_generator"],
     "modelscope": ["modelscope"],
     "quality": ["ruff"],
-    "torch_npu": ["torch==2.1.0", "torch_npu==2.1.0.post3", "decorator"]
 }
 
 

src/llamafactory/data/template.py

@@ -822,6 +822,15 @@ _register_template(
 )
 
 
+_register_template(
+    name="telechat",
+    format_user=StringFormatter(slots=["<_user>{{content}}<_bot>"]),
+    format_system=StringFormatter(slots=["<_system>{{content}}<_end>"]),
+    stop_words=["<_end>"],
+    replace_eos=True,
+)
+
+
 _register_template(
     name="vicuna",
     format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),
@@ -918,13 +927,3 @@ _register_template(
     format_user=StringFormatter(slots=["<human>:{{content}}\n<bot>:"]),
     format_separator=EmptyFormatter(slots=["\n"]),
 )
-
-
-_register_template(
-    name="telechat",
-    format_user=StringFormatter(slots=["<_user>{{content}}<_bot>"]),
-    format_system=StringFormatter(slots=["<_system>{{content}}<_end>"]),
-    default_system="",
-    stop_words=["<_end>"],
-    replace_eos=True,
-)

src/llamafactory/extras/constants.py

@@ -1095,6 +1095,26 @@ register_model_group(
 )
 
 
+register_model_group(
+    models={
+        "TeleChat-7B-Chat": {
+            DownloadSource.DEFAULT: "Tele-AI/telechat-7B",
+            DownloadSource.MODELSCOPE: "TeleAI/telechat-7B",
+        },
+        "TeleChat-12B-Chat": {
+            DownloadSource.DEFAULT: "Tele-AI/TeleChat-12B",
+            DownloadSource.MODELSCOPE: "TeleAI/TeleChat-12B",
+        },
+        "TeleChat-12B-v2-Chat": {
+            DownloadSource.DEFAULT: "Tele-AI/TeleChat-12B-v2",
+            DownloadSource.MODELSCOPE: "TeleAI/TeleChat-12B-v2",
+        },
+    },
+    module="query,key_value",
+    template="telechat",
+)
+
+
 register_model_group(
     models={
         "Vicuna1.5-7B-Chat": {
@@ -1355,19 +1375,3 @@ register_model_group(
     },
     template="zephyr",
 )
-
-
-register_model_group(
-    models={
-        "TeleChat-12B-Chat": {
-            DownloadSource.DEFAULT: "Tele-AI/TeleChat-12B",
-            DownloadSource.MODELSCOPE: "TeleAI/TeleChat-12B",
-        },
-        "TeleChat-12B-v2-Chat": {
-            DownloadSource.DEFAULT: "Tele-AI/TeleChat-12B-v2",
-            DownloadSource.MODELSCOPE: "TeleAI/TeleChat-12B-v2",
-        },
-    },
-    module='query,key_value',
-    template="telechat",
-)