Felipe97/llama-cpp-compiled

1from __future__ import annotations2 3from typing import TYPE_CHECKING4 5if TYPE_CHECKING:6    from torch import Tensor7 8from .base import ModelBase, TextModel, gguf9 10from .deepseek import DeepseekV2Model11from .llama import LlamaModel12 13 14@ModelBase.register(15    "Mistral3ForConditionalGeneration",16    "Ministral3ForCausalLM",17)18@ModelBase.example("mistralai/Mistral-Small-3.1-24B-Instruct-2503", "hf-tiny-v2/tiny-random-Ministral3ForCausalLM")19class Mistral3Model(TextModel):20    class Ministral3Model(LlamaModel):21        model_arch = gguf.MODEL_ARCH.MISTRAL322 23        def set_gguf_parameters(self):24            super().set_gguf_parameters()25            rope_params = self.rope_parameters26            if self.hparams.get("model_type") == "ministral3":27                assert rope_params, "ministral3 must have 'rope_parameters' config"28                assert rope_params["rope_type"] == "yarn", "ministral3 rope_type must be 'yarn'"29                self.gguf_writer.add_rope_scaling_yarn_log_mul(rope_params["mscale_all_dim"])30                self.gguf_writer.add_attn_temperature_scale(rope_params["llama_4_scaling_beta"])31 32    class Mistral4Model(DeepseekV2Model):33        model_arch = gguf.MODEL_ARCH.MISTRAL434        skip_mtp = False # model contains no MTP layers, so no need to skip35        merge_expert = False # experts are already stacked as 3D36 37        def modify_tensors(self, data_torch, name, bid):38            if name.endswith(".down_proj") or name.endswith(".gate_up_proj"):39                name = name + ".weight"40            yield from super().modify_tensors(data_torch, name, bid)41 42    model_arch = gguf.MODEL_ARCH.MISTRAL3 # unused43    impl: TextModel44 45    def __init__(self, *args, **kwargs):46        super().__init__(*args, **kwargs)47        if self.hparams.get("model_type") == "mistral4":48            self.impl = Mistral3Model.Mistral4Model(*args, **kwargs)49        else:50            self.impl = Mistral3Model.Ministral3Model(*args, **kwargs)51 52    def set_vocab(self):53        self.impl.set_vocab()54 55    def set_gguf_parameters(self):56        self.impl.set_gguf_parameters()57 58    def modify_tensors(self, data_torch: Tensor, name: str, bid: int | None):59        yield from self.impl.modify_tensors(data_torch, name, bid)60 61    def prepare_tensors(self):62        self.impl.prepare_tensors()63 64    def write_vocab(self):65        self.impl.write_vocab()66 67    def write(self):68        self.impl.write()69