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# nemo_automodel.components.models.muse_glimmer.config

Configuration for the native AutoModel MuseGlimmer implementation.

## Module Contents

### Classes

| Name                                                                                                       | Description                                                                            |
| ---------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------- |
| [`MuseGlimmerConfig`](#nemo_automodel-components-models-muse_glimmer-config-MuseGlimmerConfig)             | Configuration accepting both legacy flat and canonical nested MuseGlimmer checkpoints. |
| [`MuseGlimmerTextConfig`](#nemo_automodel-components-models-muse_glimmer-config-MuseGlimmerTextConfig)     | Canonical nested configuration for the MuseGlimmer language backbone.                  |
| [`MuseGlimmerVisionConfig`](#nemo_automodel-components-models-muse_glimmer-config-MuseGlimmerVisionConfig) | Canonical nested configuration for the MuseGlimmer vision tower.                       |

### API

```python
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`**

---

```python
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'`

---

```python
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'`

---