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@lenml/tokenizers

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@lenml/tokenizers

a lightweight no-dependency fork of transformers.js (only tokenizers)

Source
npmnpm
Version
3.0.2
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31K
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@lenml/tokenizers

a lightweight no-dependency fork from transformers.js (only tokenizers)

  • github: https://github.com/lenML/tokenizers
  • tokenizers-arena: https://lenml.github.io/tokenizers-arena/#/side-by-side

Usage

install

npm/yarn/pnpm

npm install @lenml/tokenizers

ESM

<script type="importmap">
  {
    "imports": {
      "@lenml/tokenizers": "https://www.unpkg.com/@lenml/tokenizers@latest/dist/main.mjs"
    }
  }
</script>
<script type="module">
  import { TokenizerLoader, tokenizers } from "@lenml/tokenizers";
  console.log('@lenml/tokenizers: ',tokenizers);
</script>

load tokenizer

from json

import { TokenizerLoader } from "@lenml/tokenizers";
const tokenizer = TokenizerLoader.fromPreTrained({
    tokenizerJSON: { /* ... */ },
    tokenizerConfig: { /* ... */ }
});

from urls

import { TokenizerLoader } from "@lenml/tokenizers";
const tokenizer = await TokenizerLoader.fromPreTrainedUrls({
    tokenizerJSON: "https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1/resolve/main/tokenizer.json?download=true",
    tokenizerConfig: "https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1/resolve/main/tokenizer_config.json?download=true"
});

from pre-packaged tokenizer

import { fromPreTrained } from "@lenml/tokenizer-llama3";
const tokenizer = fromPreTrained();

chat template

const tokens = tokenizer.apply_chat_template(
  [
    {
      role: "system",
      content: "You are helpful assistant.",
    },
    {
      role: "user",
      content: "Hello, how are you?",
    },
  ]
) as number[];

const chat_content = tokenizer.decode(tokens);

console.log(chat_content);

output:

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

You are helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>

Hello, how are you?<|eot_id|><|start_header_id|>assistant<|end_header_id|>

tokenizer api

console.log(
    "encode() => ",
    tokenizer.encode("Hello, my dog is cute", null, {
        add_special_tokens: true,
    })
);
console.log(
    "_encode_text() => ",
    tokenizer._encode_text("Hello, my dog is cute")
);

fully tokenizer api: transformer.js tokenizers document

get lightweight transformers.tokenizers

In the @lenml/tokenizers package, you can get a lightweight no-dependency implementation of tokenizers:

Since all dependencies related to huggingface have been removed in this library, although the implementation is the same, it is not possible to load models using the form hf_user/repo.

import { tokenizers } from "@lenml/tokenizers";

const {
    CLIPTokenizer,
    AutoTokenizer,
    CohereTokenizer,
    VitsTokenizer,
    WhisperTokenizer,
    // ...
} = tokenizers;

License

Apache-2.0

Keywords

llama

FAQs

Package last updated on 09 Oct 2024

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