bridge.models.hy_v3.hy_v3_bridge#

Module Contents#

Classes#

HYV3Bridge

Megatron Bridge for Hy V3 MoE Causal LM.

Data#

__all__

API#

bridge.models.hy_v3.hy_v3_bridge.__all__#

[‘HYV3Bridge’]

class bridge.models.hy_v3.hy_v3_bridge.HYV3Bridge#

Bases: megatron.bridge.models.conversion.model_bridge.MegatronModelBridge

Megatron Bridge for Hy V3 MoE Causal LM.

This bridge handles the conversion between HuggingFace HYV3ForCausalLM and Megatron-Core GPTModel formats. Hy V3 is a fine-grained MoE decoder with GQA + QK layernorm, dense-first layer freq, sigmoid router with per-expert bias, shared experts, and grouped-GEMM routed experts.

.. rubric:: Example

from megatron.bridge import AutoBridge bridge = AutoBridge.from_hf_pretrained(“tencent/Hy3-preview-Base”) provider = bridge.to_megatron_provider()

provider_bridge(
hf_pretrained: megatron.bridge.models.hf_pretrained.causal_lm.PreTrainedCausalLM,
) → megatron.bridge.models.gpt_provider.GPTModelProvider#

Convert HuggingFace Hy V3 config to GPTModelProvider.

classmethod megatron_to_hf_config(
provider: megatron.bridge.models.gpt_provider.GPTModelProvider,
) → dict#

Convert Megatron provider config to HuggingFace HYV3Config dict.

mapping_registry() → megatron.bridge.models.conversion.mapping_registry.MegatronMappingRegistry#