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Fix Mixtral conversion #365

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Merged
jlamypoirier merged 1 commit into from
Sep 19, 2025
Merged

Fix Mixtral conversion #365

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12 changes: 8 additions & 4 deletions fast_llm/models/gpt/conversion/llama.py
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Original file line number Diff line number Diff line change
Expand Up @@ -354,6 +354,10 @@ class LlamaBlockConverter:
mixer_converter_class: typing.ClassVar[type[LlamaAttentionConverter]] = LlamaAttentionConverter
mlp_converter_class: typing.ClassVar[type[LlamaMLPConverter]] = LlamaMLPConverter
normalization_converter_class: typing.ClassVar[type[LlamaNormalizationConverter]] = LlamaNormalizationConverter
hf_mixer_name: typing.ClassVar[str] = "self_attn"
hf_mlp_name: typing.ClassVar[str] = "mlp"
hf_norm_1_name: typing.ClassVar[str] = "input_layernorm"
hf_norm_2_name: typing.ClassVar[str] = "post_attention_layernorm"

@classmethod
def import_config(cls, config: dict, hidden_size: int) -> dict:
Expand All @@ -380,25 +384,25 @@ def get_converters(
*cls.mixer_converter_class.get_converters(
config.mixer,
f"{fast_llm_prefix}.mixer",
f"{hf_prefix}.self_attn",
f"{hf_prefix}.{cls.hf_mixer_name}",
drop_on_export,
),
*cls.mlp_converter_class.get_converters(
config.mlp,
f"{fast_llm_prefix}.mlp",
f"{hf_prefix}.mlp",
f"{hf_prefix}.{cls.hf_mlp_name}",
drop_on_export,
),
*cls.normalization_converter_class.get_converters(
config.normalization,
f"{fast_llm_prefix}.norm_1",
f"{hf_prefix}.input_layernorm",
f"{hf_prefix}.{cls.hf_norm_1_name}",
drop_on_export,
),
*cls.normalization_converter_class.get_converters(
config.normalization,
f"{fast_llm_prefix}.norm_2",
f"{hf_prefix}.post_attention_layernorm",
f"{hf_prefix}.{cls.hf_norm_2_name}",
drop_on_export,
),
]
Expand Down
21 changes: 17 additions & 4 deletions fast_llm/models/gpt/conversion/mixtral.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
from fast_llm.engine.checkpoint.external import SplitWeightConverter, WeightConverter
from fast_llm.layers.decoder.mlp.config import MoEMLPConfig
from fast_llm.models.gpt.conversion.config import MixtralCheckpointFormat
from fast_llm.models.gpt.conversion.llama import LlamaMLPConverter, get_weight_and_bias_converters
from fast_llm.models.gpt.conversion.llama import LlamaMLPConverter, MLPLayer2Converter, get_weight_and_bias_converters
from fast_llm.models.gpt.conversion.mistral import (
MistralBaseModelConverter,
MistralBlockConverter,
Expand Down Expand Up @@ -50,16 +50,29 @@ def get_converters(
return [
*get_weight_and_bias_converters(
f"{fast_llm_prefix}.router",
() if drop_on_export else (f"{hf_prefix}.router",),
config.add_linear_biases,
f"{hf_prefix}.gate",
False,
drop_on_export=drop_on_export,
),
*get_weight_and_bias_converters(
f"{fast_llm_prefix}.layer_1",
tuple(f"{hf_prefix}.experts.{i}.{w}" for i in range(config.experts) for w in ("w1", "w3")),
False,
SplitWeightConverter,
drop_on_export=drop_on_export,
),
*super().get_converters(config, fast_llm_prefix, hf_prefix, drop_on_export=drop_on_export),
*get_weight_and_bias_converters(
f"{fast_llm_prefix}.layer_2",
tuple(f"{hf_prefix}.experts.{i}.w2" for i in range(config.experts)),
False,
MLPLayer2Converter,
drop_on_export=drop_on_export,
),
]


class MixtralBlockConverter(MistralBlockConverter):
hf_mlp_name: typing.ClassVar[str] = "block_sparse_moe"
mlp_converter_class: typing.ClassVar[type[MixtralMLPConverter]] = MixtralMLPConverter


Expand Down