diff --git a/docs/source/zh/_toctree.yml b/docs/source/zh/_toctree.yml
index 7ebddf0339146e..3c6c0a203c18df 100644
--- a/docs/source/zh/_toctree.yml
+++ b/docs/source/zh/_toctree.yml
@@ -52,6 +52,8 @@
     title: 导出为 TorchScript
   - local: gguf
     title: 与 GGUF 格式的互操作性
+  - local: tiktoken
+    title: 与 Tiktoken 文件的互操作性
   title: 开发者指南
 - sections:
   - local: performance
diff --git a/docs/source/zh/tiktoken.md b/docs/source/zh/tiktoken.md
new file mode 100644
index 00000000000000..c8ef6b129eccc0
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+++ b/docs/source/zh/tiktoken.md
@@ -0,0 +1,55 @@
+<!--Copyright 2024 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+``
+⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
+rendered properly in your Markdown viewer.
+
+-->
+
+# Transformers与Tiktonken的互操作性
+
+在🤗 transformers中，当使用`from_pretrained`方法从Hub加载模型时，如果模型包含tiktoken格式的`tokenizer.model`文件，框架可以无缝支持tiktoken模型文件，并自动将其转换为我们的[快速词符化器](https://huggingface.co/docs/transformers/main/en/main_classes/tokenizer#transformers.PreTrainedTokenizerFast)。
+
+### 已知包含`tiktoken.model`文件发布的模型：
+    - gpt2
+    - llama3
+
+## 使用示例
+
+为了在transformers中正确加载`tiktoken`文件，请确保`tiktoken.model`文件是tiktoken格式的，并且会在加载`from_pretrained`时自动加载。以下展示如何从同一个文件中加载词符化器(tokenizer)和模型：
+
+```py
+from transformers import AutoTokenizer
+
+model_id = "meta-llama/Meta-Llama-3-8B-Instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_id, subfolder="original") 
+```
+## 创建tiktoken词符化器(tokenizer)
+
+`tokenizer.model`文件中不包含任何额外的词符(token)或模式字符串(pattern strings)的信息。如果这些信息很重要，需要将词符化器(tokenizer)转换为适用于[`PreTrainedTokenizerFast`]类的`tokenizer.json`格式。
+
+使用[tiktoken.get_encoding](https://github.com/openai/tiktoken/blob/63527649963def8c759b0f91f2eb69a40934e468/tiktoken/registry.py#L63)生成`tokenizer.model`文件，再使用[`convert_tiktoken_to_fast`]函数将其转换为`tokenizer.json`文件。
+
+```py
+
+from transformers.integrations.tiktoken import convert_tiktoken_to_fast
+from tiktoken import get_encoding
+
+# You can load your custom encoding or the one provided by OpenAI
+encoding = get_encoding("gpt2")
+convert_tiktoken_to_fast(encoding, "config/save/dir")
+```
+
+生成的`tokenizer.json`文件将被保存到指定的目录，并且可以通过[`PreTrainedTokenizerFast`]类来加载。
+
+```py
+tokenizer = PreTrainedTokenizerFast.from_pretrained("config/save/dir")
+```