Update README.md

README.md

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 This model was converted to GGUF format from [`THUDM/GLM-Z1-32B-0414`](https://huggingface.co/THUDM/GLM-Z1-32B-0414) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/THUDM/GLM-Z1-32B-0414) for more details on the model.
 
+---
+The GLM family welcomes a new generation of open-source models, the GLM-4-32B-0414
+ series, featuring 32 billion parameters. Its performance is comparable 
+to OpenAI's GPT series and DeepSeek's V3/R1 series, and it supports very
+ user-friendly local deployment features. GLM-4-32B-Base-0414 was 
+pre-trained on 15T of high-quality data, including a large amount of 
+reasoning-type synthetic data, laying the foundation for subsequent 
+reinforcement learning extensions. In the post-training stage, in 
+addition to human preference alignment for dialogue scenarios, we also 
+enhanced the model's performance in instruction following, engineering 
+code, and function calling using techniques such as rejection sampling 
+and reinforcement learning, strengthening the atomic capabilities 
+required for agent tasks. GLM-4-32B-0414 achieves good results in areas 
+such as engineering code, Artifact generation, function calling, 
+search-based Q&A, and report generation. Some benchmarks even rival 
+larger models like GPT-4o and DeepSeek-V3-0324 (671B).
+
+GLM-Z1-32B-0414 is a reasoning model with deep thinking capabilities.
+ This was developed based on GLM-4-32B-0414 through cold start and 
+extended reinforcement learning, as well as further training of the 
+model on tasks involving mathematics, code, and logic. Compared to the 
+base model, GLM-Z1-32B-0414 significantly improves mathematical 
+abilities and the capability to solve complex tasks. During the training
+ process, we also introduced general reinforcement learning based on 
+pairwise ranking feedback, further enhancing the model's general 
+capabilities.
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)