remove GLM-4 quantization wrong Code

[zRzRzRzRzRzRzR]

need to remove this line

[gemini-code-assist]

Code Review

This pull request aims to fix an issue with quantization for the GLM-4.5 MoE model by removing the quant_config parameter from the VocabParallelEmbedding layer. While this may resolve issues for certain quantization methods, I've identified a critical issue where this change will break support for GGUF-quantized models. My review includes a detailed explanation of the problem and suggests a more robust, conditional approach to ensure all supported quantization formats continue to work correctly.

[gemini-code-assist]

This change unconditionally removes quant_config from the VocabParallelEmbedding layer, which will disable quantization for token embeddings. While this might be the intended fix for certain quantization methods (e.g., GPTQ, AWQ), it will break support for others that rely on quantizing the embedding layer, such as GGUF.

When quant_config is not provided, VocabParallelEmbedding defaults to UnquantizedEmbeddingMethod. This method does not create the necessary parameters (like qweight) for GGUF, which will lead to failures during weight loading for GGUF-quantized GLM-4.5 models.

This is a critical issue as it silently disables a supported quantization format for this model.

A more robust solution would be to conditionally pass quant_config based on the quantization method. For instance, you could check if quant_config.get_name() == 'gguf' and only pass the config in that case, preserving the fix for other methods while maintaining GGUF compatibility.

[DarkLight1337]

Next time please sign off your commits using -s flag in git commit

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[zRzRzRzRzRzRzR]

This PR does not need to be merged first, as we have found some potential issues in the quantized model
@Isotr0py we may need to do some further checks. Regarding FlashInfer, some errors may occur.
Additionally, since the model name has been modified, the tool calls and reason parser in the registry need to be renamed.

[zRzRzRzRzRzRzR]

This PR can be merged first; we haven't found any FC issues yet. If we find and fix them, we will submit a new PR.
Regarding quantization, there are no issues for now,