Mistral3 text encoder configuration for full Flux2.
Classes¶
dataclass
¶
Mistral3TextArchConfig(stacked_params_mapping: list[tuple[str, str, str]] = list(), architectures: list[str] = (lambda: ['Mistral3ForConditionalGeneration'])(), _supported_attention_backends: tuple[AttentionBackendEnum, ...] = (FLASH_ATTN, TORCH_SDPA), output_hidden_states: bool = True, use_return_dict: bool = True, vocab_size: int = 0, hidden_size: int = 5120, num_hidden_layers: int = 40, num_attention_heads: int = 0, pad_token_id: int = 0, eos_token_id: int = 0, text_len: int = 512, hidden_state_skip_layer: int = 0, decoder_start_token_id: int = 0, output_past: bool = True, scalable_attention: bool = True, tie_word_embeddings: bool = False, tokenizer_kwargs: dict[str, Any] = dict(), _fsdp_shard_conditions: list = (lambda: [])(), require_processor: bool = True)
Bases: TextEncoderArchConfig
Architecture config for the Mistral3 text encoder used by full Flux2.
dataclass
¶
Mistral3TextConfig(arch_config: TextEncoderArchConfig = Mistral3TextArchConfig(), prefix: str = 'mistral3', quant_config: QuantizationConfig | None = None, lora_config: Any | None = None, is_chat_model: bool = True, treat_empty_as_dot: bool = False)
Bases: TextEncoderConfig
Top-level config for the Mistral3 full Flux2 text encoder.