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fix typos (#38336)

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* Update video_processor.md

* Update deepseek_v3.md
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Ragnar
2025-05-26 16:42:37 +02:00
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parent 8b03c8eaf2
commit 63964b7c67
2 changed files with 3 additions and 3 deletions
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docs/source/en/main_classes/video_processor.md
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@@ -21,7 +21,7 @@ A **Video Processor** is a utility responsible for preparing input features for
The video processor extends the functionality of image processors by allowing Vision Large Language Models (VLMs) to handle videos with a distinct set of arguments compared to images. It serves as the bridge between raw video data and the model, ensuring that input features are optimized for the VLM.
When adding a new VLM or updating an existing one to enable distinct video preprocessing, saving and reloading the processor configuration will store the video related arguments in a dedicated file named `video_preprocessing_config.json`. Don't worry if you haven't upadted your VLM, the processor will try to load video related configurations from a file named `preprocessing_config.json`.
When adding a new VLM or updating an existing one to enable distinct video preprocessing, saving and reloading the processor configuration will store the video related arguments in a dedicated file named `video_preprocessing_config.json`. Don't worry if you haven't updated your VLM, the processor will try to load video related configurations from a file named `preprocessing_config.json`.
### Usage Example

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docs/source/en/model_doc/deepseek_v3.md
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@@ -28,8 +28,8 @@ We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 67
We are super happy to make this code community-powered, and would love to see how you can best optimize the following:
- current implementation uses the "naive" attention compution (so not really MLA)
- current implementation loops through the experts. This should be replaced. Pointers to use `get_packed_weights` from `intetrations/tensor_parallel`.
- current implementation uses the eleuther formula for ROPE, using the orginal one would be more efficient! (should still follow our API)
- current implementation loops through the experts. This should be replaced. Pointers to use `get_packed_weights` from `integrations/tensor_parallel`.
- current implementation uses the eleuther formula for ROPE, using the original one would be more efficient! (should still follow our API)
- static cache is not supported (this should be just a generation config issue / config shape issues)
### Usage tips