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# This file is distributed under the same license as the Xinference package.
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#: ../../source/models/model_abilities/video.rst:5
msgid "Video (Experimental)"
msgstr "影片（實驗性質）"

#: ../../source/models/model_abilities/video.rst:7
msgid "Learn how to generate videos with Xinference."
msgstr "學習如何使用 Xinference 生成影片"

#: ../../source/models/model_abilities/video.rst:11
msgid "Introduction"
msgstr "Introduction"

#: ../../source/models/model_abilities/video.rst:14
msgid "The Video API provides the ability to interact with videos:"
msgstr "Video API 提供了和影片互動的方式："

#: ../../source/models/model_abilities/video.rst:17
msgid ""
"The text-to-video endpoint create videos from scratch based on a text "
"prompt."
msgstr "Text-to-video 端點會根據一段文字提示，從頭開始建立影片。"

#: ../../source/models/model_abilities/video.rst:18
msgid ""
"The image-to-video endpoint create videos from scratch based on an input "
"image."
msgstr "Image-to-video 端點將一張圖片從頭開始創建影片"

#: ../../source/models/model_abilities/video.rst:19
msgid ""
"The firstlastframe-to-video endpoint creates videos based on the transition "
"between a first and a last frame."
msgstr "firstlastframe-to-video 介面根據首幀與尾幀之間的過渡生成影片。"

#: ../../source/models/model_abilities/video.rst:39
msgid "Supported models"
msgstr "支援的模型列表"

#: ../../source/models/model_abilities/video.rst:41
msgid ""
"The text-to-video API is supported with the following models in Xinference:"
msgstr "Text-to-video API 在 Xinference 中支援以下模型："

#: ../../source/models/model_abilities/video.rst:43
msgid ":ref:`CogVideoX-2b <models_builtin_cogvideox-2b>`"
msgstr ""

#: ../../source/models/model_abilities/video.rst:44
msgid ":ref:`CogVideoX-5b <models_builtin_cogvideox-5b>`"
msgstr ""

#: ../../source/models/model_abilities/video.rst:45
msgid ":ref:`HunyuanVideo <models_builtin_hunyuanvideo>`"
msgstr ""

#: ../../source/models/model_abilities/video.rst:46
msgid ":ref:`Wan2.1-1.3B <models_builtin_wan2.1-1.3b>`"
msgstr ""

#: ../../source/models/model_abilities/video.rst:47
msgid ":ref:`Wan2.1-14B <models_builtin_wan2.1-14b>`"
msgstr ""

#: ../../source/models/model_abilities/video.rst:49
msgid ""
"The image-to-video API is supported with the following models in Xinference:"
msgstr "Image-to-video API 在 Xinference 中支援以下模型："

#: ../../source/models/model_abilities/video.rst:51
msgid ":ref:`Wan2.1-i2v-14B-480p <models_builtin_wan2.1-i2v-14b-480p>`"
msgstr ""

#: ../../source/models/model_abilities/video.rst:52
msgid ":ref:`Wan2.1-i2v-14B-720p <models_builtin_wan2.1-i2v-14b-720p>`"
msgstr ""

#: ../../source/models/model_abilities/video.rst:54
msgid ""
"The firstlastframe-to-video API is supported with the following models in "
"Xinference:"
msgstr "Xinference 中支援以下模型使用 firstlastframe-to-video 介面："

#: ../../source/models/model_abilities/video.rst:56
msgid ":ref:`Wan2.1-flf2v-14B-720p <models_builtin_wan2.1-flf2v-14b-720p>`"
msgstr ""

#: ../../source/models/model_abilities/video.rst:59
msgid "Quickstart"
msgstr "快速入門"

#: ../../source/models/model_abilities/video.rst:62
msgid "Text-to-video"
msgstr "文生影片"

#: ../../source/models/model_abilities/video.rst:64
msgid ""
"You can try text-to-video API out either via cURL, or Xinference's python "
"client:"
msgstr "可以透過 cURL 或 Xinference 的方式嘗試使用 text-to-video API"

#: ../../source/models/model_abilities/video.rst:91
msgid "Image-to-video"
msgstr "圖生影片"

#: ../../source/models/model_abilities/video.rst:93
msgid ""
"You can try image-to-video API out either via cURL, or Xinference's python "
"client:"
msgstr "可透過 cURL 或 Xinference 的方式嘗試使用 image-to-video API"

#: ../../source/models/model_abilities/video.rst:118
msgid "FirstLastFrame-to-video"
msgstr "首尾幀生影片"

#: ../../source/models/model_abilities/video.rst:120
msgid ""
"You can try firstlastframe-to-video API out either via cURL, or Xinference's"
" python client:"
msgstr "你可以透過 cURL 或 Xinference 的 Python 客戶端來體驗 firstlastframe-to-video 介面。"

#: ../../source/models/model_abilities/video.rst:147
msgid "Memory optimization"
msgstr "記憶體優化"

#: ../../source/models/model_abilities/video.rst:149
msgid ""
"Video generation will occupy huge GPU memory, for instance, running "
"CogVideoX may require up to around 35 GB GPU memory."
msgstr "影片生成會佔用大量視訊記憶體，舉例來說，執行 CogVideoX 可能會使用到大約 35 GB 的視訊記憶體。"

#: ../../source/models/model_abilities/video.rst:152
msgid ""
"Xinference supports several options to optimize video model memory (VRAM) "
"usage."
msgstr "Xinference 支援若干選項，來優化影片模型顯存（VRAM）使用。"

#: ../../source/models/model_abilities/video.rst:154
msgid "CPU offloading or block level group offloading."
msgstr "CPU 卸載或區塊層級分組卸載。"

#: ../../source/models/model_abilities/video.rst:155
msgid "Layerwise casting."
msgstr "逐層類型轉換（Layerwise casting）。"

#: ../../source/models/model_abilities/video.rst:159
msgid ""
"CPU offloading and Block Level Group Offloading cannot be enabled at the "
"same time, but layerwise casting can be used in combination with either of "
"them."
msgstr "CPU 卸載和塊級分組卸載不能同時開啟，但逐層類型轉換可以與其中之一配合使用。"

#: ../../source/models/model_abilities/video.rst:163
msgid "CPU offloading"
msgstr "CPU 卸載"

#: ../../source/models/model_abilities/video.rst:165
msgid ""
"CPU offloading keeps the model weights on the CPU and only loads them to the"
" GPU when a forward pass needs to be executed. It is suitable for scenarios "
"with extremely limited GPU memory, but it has a significant impact on "
"performance."
msgstr "CPU 卸載會將模型權重保留在 CPU 上，僅在執行前向傳播時才載入到 GPU。適用於顯存極其有限的場景，但對效能影響較大。"

#: ../../source/models/model_abilities/video.rst:169
msgid ""
"When running on GPU whose memory is less than 24 GB, we recommend to add "
"``--cpu_offload True`` when launching model. For Web UI, add an extra "
"option, ``cpu_offload`` with value set to ``True``."
msgstr ""
"当使用显存小于 24 GB 的 GPU 时，建议在启动模型时添加 ``--cpu_offload True``。对于 Web UI，可添加额外选项 "
"``cpu_offload``，值设为 ``True``。"

#: ../../source/models/model_abilities/video.rst:178
msgid "Block Level Group Offloading"
msgstr "塊級分組卸載"

#: ../../source/models/model_abilities/video.rst:180
msgid ""
"Block Level Group Offloading groups multiple internal layers of the model "
"(such as ``torch.nn.ModuleList`` or ``torch.nn.Sequential``) and loads these"
" groups from the CPU to the GPU as needed during inference. Compared to CPU "
"offloading, it uses more memory but has less impact on performance."
msgstr ""
"塊級分組卸載將模型的多個內部層（如 ``torch.nn.ModuleList`` 或 "
"``torch.nn.Sequential``）分組，並根據需要在推理過程中將這些分組從 CPU 載入到 GPU。與 CPU "
"卸載相比，它使用更多的記憶體，但對效能的影響更小。"

#: ../../source/models/model_abilities/video.rst:184
msgid ""
"For the command line, add the ``--group_offload True`` option; for the Web "
"UI, add an additional option ``group_offload`` with the value set to "
"``True``."
msgstr ""
"針對命令列，添加 ``--group_offload True`` 選項；對於 Web UI，添加一個額外選項 "
"``group_offload``，數值設為 ``True``。"

#: ../../source/models/model_abilities/video.rst:187
msgid ""
"We can speed up group offloading inference, by enabling the use of CUDA "
"streams. However, using CUDA streams requires moving the model parameters "
"into pinned memory. This allocation is handled by Pytorch under the hood, "
"and can result in a significant spike in CPU RAM usage. Please consider this"
" option if your CPU RAM is atleast 2X the size of the model you are group "
"offloading. Enable CUDA streams via adding ``--use_stream True`` for command"
" line; for the Web UI, add an additional option ``use_stream`` with the "
"value set to ``True``."
msgstr ""
"通過啟用 CUDA 串流，我們可以加速分組卸載推理。然而，使用 CUDA 串流需要將模型參數移動到固定記憶體中。這項分配由 PyTorch "
"在後台處理，並可能導致 CPU RAM 使用量顯著增加。如果您的 CPU RAM 至少是模型大小的兩倍，請考慮使用此選項。透過在命令列中加入 "
"``--use_stream True`` 啟用 CUDA 串流；對於 Web UI，則添加一個額外選項 ``use_stream``，並將值設為 "
"``True``。"

#: ../../source/models/model_abilities/video.rst:199
msgid "Applying Layerwise Casting to the Transformer"
msgstr "將逐層類型轉換應用於 Transformer"

#: ../../source/models/model_abilities/video.rst:201
msgid ""
"Layerwise casting will downcast each layer’s weights to "
"``torch.float8_e4m3fn``, temporarily upcast to ``torch.bfloat16`` during the"
" forward pass of the layer, then revert to ``torch.float8_e4m3fn`` "
"afterward. This approach reduces memory requirements by approximately 50% "
"while introducing a minor quality reduction in the generated video due to "
"the precision trade-off. Enable layerwise casting via adding "
"``--layerwise_cast True`` for command line; for the Web UI, add an "
"additional option ``layerwise_cast`` with the value set to ``True``."
msgstr ""
"逐層型別轉換會將每個層的權重降級為 ``torch.float8_e4m3fn``，在層的前向傳播過程中暫時升級為 "
"``torch.bfloat16``，然後在之後恢復為 ``torch.float8_e4m3fn``。這種方法將記憶體需求減少約 "
"50%，同時由於精度折衷，生成的影片品質會略有下降。透過在命令列中添加 ``--layerwise_cast True`` 來啟用逐層型別轉換；對於 "
"Web UI，添加一個額外選項 ``layerwise_cast``，值設為 ``True``。"

#: ../../source/models/model_abilities/video.rst:208
msgid "This example will require 20GB of VRAM."
msgstr "此範例將需要 20GB 的視訊記憶體。"

#~ msgid "OpenAI-compatible ENDPOINT"
#~ msgstr "OpenAI 相容端點"

#~ msgid "API"
#~ msgstr ""

#~ msgid "Endpoint"
#~ msgstr "端點"

#~ msgid "Text-to-Video API"
#~ msgstr "Text-to-Video API"

#~ msgid "/v1/video/generations"
#~ msgstr ""

#~ msgid "Image-to-Video API"
#~ msgstr "圖生影片 API"

#~ msgid "/v1/video/generations/image"
#~ msgstr ""
