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GeezerVison is showing github.com — Support DraftRetriever datastore read/write for large tokenizers and vocabulary sizes (i.e. llama3+) by scandukuri · Pull Request #23 · FasterDecoding/REST

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@scandukuri

@scandukuri scandukuri commented Nov 13, 2024

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Here we make the necessary changes to read and write suffixes to memory and file for large tokenizers; the original implementation only supported token IDs up to Rust u16::MAX (65,535).

Crucially, using Rust i32 for reading and writing individual token IDs (instead of u16 originally) allows the tool to support token IDs of up to Rust i32::MAX (2,147,483,647), and still allows negative placeholder IDs for padding in the implementation like -2.

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scandukuri added 2 commits November 12, 2024 22:30
@scandukuri
support large vocab sizes (i.e. llama3) for DraftRetriever datastore
05f57b0
@scandukuri
updates comments to explain implementation changes
9b9cebd
@zhenyuhe00

zhenyuhe00 commented Nov 20, 2024

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Hi,
Thank you for the fix. Would you consider creating a new branch? The change from "u16" to "i32" isn't needed for models with small vocabulary size and would increase disk storage usage unnecessarily.

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@scandukuri

scandukuri commented Nov 20, 2024 via email •
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Yes! Can make a ‘llama3’ branch. I can make the existing changes (DraftRetriever) + the necessary changes to modeling_llama_kv.py.
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@zhenyuhe00

zhenyuhe00 commented Nov 20, 2024

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That sounds great! Appreciate your effort.

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@scandukuri scandukuri closed this Nov 20, 2024
@scandukuri scandukuri mentioned this pull request Nov 20, 2024
Support DraftRetriever datastore read/write for large vocab sizes (i.e. llama3+) and REST inference for llama3 #24
Merged
@csAugust csAugust mentioned this pull request Nov 30, 2024
Llama3 Branch Still Suffers Segmentation Fault When Generating Datastore Using Qwen2.5 #26
Closed
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@scandukuri @zhenyuhe00
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