update

README.md

@@ -1,3 +1,43 @@
----
-license: mit
----
+---
+license: mit
+language:
+- en
+- zh
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# GLM-4.5-Air
+
+<div align="center">
+<img src=https://raw.githubusercontent.com/zai-org/GLM-4.5/a53b7744b59c7786941c11d70a57d84965b54bf9/resources/logo.svg?token=AWHLTA6WJTQOTAD35SI4PV3IQ5U7Y width="15%"/>
+</div>
+<p align="center">
+    👋 Join our <a href="https://discord.gg/QR7SARHRxK" target="_blank">Discord</a> community.
+    <br>
+    📖 Check out the GLM-4.5 <a href="https://z.ai/blog/glm-4.5" target="_blank">technical blog</a>.
+    <br>
+    📍 Use GLM-4.5 API services on <a href="https://docs.bigmodel.cn/cn/guide/models/text/glm-4.5">Zhipu AI Open Platform</a>.
+    <br>
+    👉 One click to <a href="https://chat.z.ai">GLM-4.5</a>.
+</p>
+  
+## Model Introduction
+
+The **GLM-4.5** series models are foundation models designed for intelligent agents. GLM-4.5 has **355** billion total parameters with **32** billion active parameters, while GLM-4.5-Air adopts a more compact design with **106** billion total parameters and **12** billion active parameters. GLM-4.5 models unify reasoning, coding, and intelligent agent capabilities to meet the complex demands of intelligent agent applications.
+
+Both GLM-4.5 and GLM-4.5-Air are hybrid reasoning models that provide two modes: thinking mode for complex reasoning and tool usage, and non-thinking mode for immediate responses.
+
+We have open-sourced the base models, hybrid reasoning models, and FP8 versions of the hybrid reasoning models for both GLM-4.5 and GLM-4.5-Air. They are released under the MIT open-source license and can be used commercially and for secondary development.
+
+As demonstrated in our comprehensive evaluation across 12 industry-standard benchmarks, GLM-4.5 achieves exceptional performance with a score of **63.2**, in the **3rd** place among all the proprietary and open-source  models. Notably, GLM-4.5-Air delivers competitive results at **59.8** while maintaining superior efficiency.
+
+![bench](https://raw.githubusercontent.com/zai-org/GLM-4.5/refs/heads/main/resources/bench.png)
+
+For more eval results, show cases, and technical details, please visit our [technical report](For more eval results, show cases, and technical details, please visit our [technical report](https://z.ai/blog/glm-4.5).
+
+The model code, tool parser and reasoning parser can be found in the implementation of [transformers](https://github.com/huggingface/transformers/tree/main/src/transformers/models/glm4_moe), [vLLM](https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/models/glm4_moe_mtp.py) and [SGLang](https://github.com/sgl-project/sglang/blob/main/python/sglang/srt/models/glm4_moe.py).
+
+## Quick Start
+
+Please refer our [github page](https://github.com/zai-org/GLM-4.5) for more detail.

generation_config.json

@@ -0,0 +1,10 @@
+{
+  "_from_model_config": true,
+  "eos_token_id": [
+    151329,
+    151336,
+    151338
+  ],
+  "pad_token_id": 151329,
+  "transformers_version": "4.54.0"
+}