model: support Ministral3 #17644
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model: support Ministral3 #17644
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ngxson
commented
Dec 1, 2025
| @ModelBase.register("Mistral3ForConditionalGeneration") | ||
| class Mistral3Model(LlamaModel): | ||
| model_arch = gguf.MODEL_ARCH.LLAMA | ||
| model_arch = gguf.MODEL_ARCH.MISTRAL3 |
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Note for maintainers: while the ministral3 and the old mistral models have almost the same cgraph, the hparams handling in llama_model::load_hparams is quite more complicated. Therefore, it's better to separate the 2 archs to make it more readable.
This also make the code to be more future-proof, in case future mistral models become significantly more complicated than the traditional llama arch.
ngxson
commented
Dec 1, 2025
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| # for compatibility, we use LLAMA arch for older models | ||
| # TODO: remove this once everyone has migrated to newer version of llama.cpp | ||
| if self.hparams.get("model_type") != "ministral3": | ||
| self.model_arch = gguf.MODEL_ARCH.LLAMA | ||
| self.gguf_writer.arch = str(self.model_arch) | ||
| self.gguf_writer.add_architecture() | ||
| self.tensor_map = gguf.get_tensor_name_map(self.model_arch, self.block_count) |
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I think a time frame of ~1 week to remove this could be a reasonable timeline to remove this.
This is for the case where users using new version of script (i.e. via gguf-my-repo) to convert old models, while their local llama.cpp version probably not yet up-to-date
ggerganov
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Dec 1, 2025
CISC
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Dec 1, 2025
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
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Ref upstream PR: huggingface/transformers#42498
Disclosure: This PR is made with collaboration from Mistral. Huge thanks to @juliendenize for coordination!
Note: The model weight is not yet released
PPl results: for the 14B model (
-Instructvariant, f16, ctx=32000, batch=8192), ppl isFinal estimate: PPL = 5.5389 +/- 0.03163