nemo_automodel.components.models.muse_glimmer.config

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Configuration for the native AutoModel MuseGlimmer implementation.

Module Contents

Classes

NameDescription
MuseGlimmerConfigConfiguration accepting both legacy flat and canonical nested MuseGlimmer checkpoints.
MuseGlimmerTextConfigCanonical nested configuration for the MuseGlimmer language backbone.
MuseGlimmerVisionConfigCanonical nested configuration for the MuseGlimmer vision tower.

API

class nemo_automodel.components.models.muse_glimmer.config.MuseGlimmerConfig(
hidden_size: int = 6656,
num_hidden_layers: int = 52,
num_attention_heads: int = 32,
num_key_value_heads: int = 2,
head_dim: int = 128,
intermediate_size: int = 19968,
vocab_size: int = 202048,
rms_norm_eps: float = 1e-05,
post_norm_eps: float = 1e-08,
rope_theta: float = 500000.0,
max_position_embeddings: int = 16384,
use_qk_norm: bool = True,
qk_scale_factor: float = 43.7840518911,
use_attn_output_gate: bool = True,
output_multiplier: float = 0.19611613513818404,
output_soft_cap_temp: float | None = 20.0,
normalize_tok_embeddings: bool = True,
sliding_window: int = 2048,
sliding_window_pattern: list[int] | None = None,
every_n_layers_nope: int = 4,
no_rope_layers: list[int] | None = None,
layer_types: list[str] | None = None,
vision_latent_dim: int = 1536,
vision_output_dim: int = 6144,
vision_layers: int = 50,
vision_heads: int = 16,
vision_mlp_ratio: float = 8960 / 1536,
vision_patch_size: int = 14,
vision_patch_temporal: int = 2,
vision_downsample_factor: int = 2,
vision_sparse_attention_factor: int = 4,
vision_pos_emb_grid_h: int = 32,
vision_pos_emb_grid_w: int = 32,
vision_adapter_dim: int = 4096,
patch_token_id: int = 200092,
image_token_id: int | None = None,
video_token_id: int = 200091,
vid_start_id: int = 200082,
vid_end_id: int = 200083,
vid_frame_sep_id: int = 200087,
video_num_frames: int = 96,
video_sampling_fps: float = 2.0,
has_vision: bool = True,
hidden_act: str = 'silu',
attention_dropout: float = 0.0,
attention_bias: bool = False,
mlp_bias: bool = False,
tie_word_embeddings: bool = False,
bos_token_id: int = 200000,
eos_token_id: int = 200001,
text_config: dict[str, typing.Any] | nemo_automodel.components.models.muse_glimmer.config.MuseGlimmerTextConfig | None = None,
vision_config: dict[str, typing.Any] | nemo_automodel.components.models.muse_glimmer.config.MuseGlimmerVisionConfig | None = None,
out_hidden_size: int | None = None,
projector_hidden_size: int | None = None,
projector_hidden_act: str = 'gelu',
kwargs: typing.Any = {}
)

Bases: PretrainedConfig

Configuration accepting both legacy flat and canonical nested MuseGlimmer checkpoints.

model_type
= 'muse_glimmer'
scale_query_by
sub_configs
class nemo_automodel.components.models.muse_glimmer.config.MuseGlimmerTextConfig(
vocab_size: int = 202048,
hidden_size: int = 6656,
intermediate_size: int = 19968,
num_hidden_layers: int = 52,
num_attention_heads: int = 32,
num_key_value_heads: int = 2,
head_dim: int = 128,
hidden_activation: str = 'silu',
max_position_embeddings: int = 131072,
initializer_range: float = 0.02,
rms_norm_eps: float = 1e-05,
post_norm_eps: float = 1e-08,
use_cache: bool = True,
attention_bias: bool = False,
attention_dropout: float = 0.0,
sliding_window: int = 2048,
layer_types: list[str] | None = None,
layer_rope_theta: list[float] | None = None,
rope_parameters: dict[str, typing.Any] | None = None,
qk_scale_factor: float = 3.87,
output_multiplier: float = 0.19611613513818404,
final_logit_softcapping: float | None = 20.0,
tie_word_embeddings: bool = False,
bos_token_id: int = 200000,
eos_token_id: int = 200001,
pad_token_id: int | None = None,
kwargs: typing.Any = {}
)

Bases: PretrainedConfig

Canonical nested configuration for the MuseGlimmer language backbone.

keys_to_ignore_at_inference
= ['past_key_values']
model_type
= 'muse_glimmer_text'
class nemo_automodel.components.models.muse_glimmer.config.MuseGlimmerVisionConfig(
hidden_size: int = 1536,
intermediate_size: int = 8960,
num_hidden_layers: int = 50,
num_attention_heads: int = 16,
hidden_act: str = 'gelu',
patch_size: int = 14,
patch_temporal: int = 2,
merge_size: int = 2,
pos_emb_height: int = 32,
pos_emb_width: int = 32,
max_position_embeddings: int = 1024,
layer_norm_eps: float = 1e-05,
layer_types: list[str] | None = None,
rope_parameters: dict[str, typing.Any] | None = None,
kwargs: typing.Any = {}
)

Bases: PretrainedConfig

Canonical nested configuration for the MuseGlimmer vision tower.

model_type
= 'muse_glimmer_vision'