mistral3 (#166)
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# Copyright © 2025 Apple Inc.
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from dataclasses import dataclass
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from typing import Optional
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import mlx.core as mx
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import mlx.nn as nn
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from mlx.utils import tree_flatten, tree_unflatten
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from . import llama
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from .base import BaseModelArgs, create_attention_mask, scaled_dot_product_attention
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@dataclass
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class ModelArgs(BaseModelArgs):
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model_type: str
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text_config: dict
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def __post_init__(self):
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self.text_config["tie_word_embeddings"] = False
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class Model(nn.Module):
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def __init__(self, args: ModelArgs):
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super().__init__()
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self.args = args
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self.model_type = args.model_type
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self.language_model = llama.Model(llama.ModelArgs.from_dict(args.text_config))
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def __call__(
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self,
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inputs: mx.array,
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cache=None,
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mask: Optional[mx.array] = None,
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):
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return self.language_model(inputs, cache=cache, mask=mask)
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def sanitize(self, weights):
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weights = tree_unflatten(list(weights.items()))
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weights.pop("vision_tower", None)
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weights.pop("multi_modal_projector", None)
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return dict(tree_flatten(weights))
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@property
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def layers(self):
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return self.language_model.model.layers
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