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# nemo_automodel.components.models.llama_bidirectional

Llama Bidirectional model for embedding and retrieval tasks.

## Submodules

* **[`nemo_automodel.components.models.llama_bidirectional.export_onnx`](/nemo-automodel/nemo_automodel/components/models/llama_bidirectional/export_onnx)**
* **[`nemo_automodel.components.models.llama_bidirectional.model`](/nemo-automodel/nemo_automodel/components/models/llama_bidirectional/model)**

## Package Contents

### Classes

| Name                                                                                                                                                     | Description                                                               |
| -------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------- |
| [`LlamaBidirectionalConfig`](#nemo_automodel-components-models-llama_bidirectional-model-LlamaBidirectionalConfig)                                       | Configuration class for LlamaBidirectionalModel.                          |
| [`LlamaBidirectionalForSequenceClassification`](#nemo_automodel-components-models-llama_bidirectional-model-LlamaBidirectionalForSequenceClassification) | Llama Bidirectional Model with a sequence classification/regression head. |
| [`LlamaBidirectionalModel`](#nemo_automodel-components-models-llama_bidirectional-model-LlamaBidirectionalModel)                                         | Llama retrieval model with a configurable attention mode.                 |

### API

```python
class nemo_automodel.components.models.llama_bidirectional.model.LlamaBidirectionalConfig(
    pooling: str = 'avg',
    temperature: float = 1.0,
    is_causal: bool = False,
    kwargs: typing.Any = {}
)
```

**Bases:** `LlamaConfig`

Configuration class for LlamaBidirectionalModel.

Extends LlamaConfig with additional parameters for bidirectional attention
and pooling configurations.

**`model_type`** `= 'llama_bidirec'`

---

```python
class nemo_automodel.components.models.llama_bidirectional.model.LlamaBidirectionalForSequenceClassification(
    config
)
```

**Bases:** `LlamaPreTrainedModel`

Llama Bidirectional Model with a sequence classification/regression head.

This model adds a classification head on top of the bidirectional Llama model
and includes configurable pooling strategies.

**`effective_score_temperature`** `float`

Return the temperature applied to score logits by this model.

---

**`model`** `= LlamaBidirectionalModel(config)`

---

**`num_labels`** `= config.num_labels`

---

**`score`**

---

```python
nemo_automodel.components.models.llama_bidirectional.model.LlamaBidirectionalForSequenceClassification._init_weights(
    module
)
```

```python
nemo_automodel.components.models.llama_bidirectional.model.LlamaBidirectionalForSequenceClassification.forward(
    input_ids: torch.LongTensor | None = None,
    attention_mask: torch.Tensor | None = None,
    position_ids: torch.LongTensor | None = None,
    past_key_values: typing.Union[transformers.cache_utils.Cache, typing.List[torch.FloatTensor]] | None = None,
    inputs_embeds: torch.FloatTensor | None = None,
    labels: torch.LongTensor | None = None,
    use_cache: bool | None = None,
    output_attentions: bool | None = None,
    output_hidden_states: bool | None = None,
    return_dict: bool | None = None,
    kwargs = {}
) -> typing.Union[typing.Tuple, transformers.modeling_outputs.SequenceClassifierOutputWithPast]
```

```python
class nemo_automodel.components.models.llama_bidirectional.model.LlamaBidirectionalModel(
    config: transformers.models.llama.configuration_llama.LlamaConfig
)
```

**Bases:** `LlamaModel`

Llama retrieval model with a configurable attention mode.

False preserves legacy bidirectional behavior; true uses the stock Llama causal mask.