easydel.modules.phi3.phi3_configuration

easydel.modules.phi3.phi3_configuration#

class easydel.modules.phi3.phi3_configuration.Phi3Config(vocab_size=32064, hidden_size=3072, intermediate_size=8192, num_hidden_layers=32, num_attention_heads=32, num_key_value_heads=None, resid_pdrop=0.0, embd_pdrop=0.0, attention_dropout=0.0, hidden_act='silu', max_position_embeddings=4096, original_max_position_embeddings=4096, initializer_range=0.02, rms_norm_eps=1e-05, use_cache=True, tie_word_embeddings=False, rope_theta=10000.0, rope_scaling=None, bos_token_id=1, eos_token_id=32000, pad_token_id=32000, sliding_window=None, bits: Optional[int] = None, gradient_checkpointing: EasyDeLGradientCheckPointers = EasyDeLGradientCheckPointers.NONE, **kwargs)[source]#

Bases: EasyDeLBaseConfig

Configuration objects inherit from [EasyDeLBaseConfig] and can be used to control the model outputs. Read the documentation from [EasyDeLBaseConfig] for more information.

Parameters

  • vocab_size (int, optional, defaults to 32064) – Vocabulary size of the Phi-3 model. Defines the number of different tokens that can be represented by the inputs_ids passed to the forward method.

  • hidden_size (int, optional, defaults to 3072) – Dimensionality of the encoder layers and the pooler layer.

  • intermediate_size (int, optional, defaults to 8192) – Dimensionality of the “intermediate” (i.e., feed-forward) layer in the Transformer encoder.

  • num_hidden_layers (int, optional, defaults to 32) – Number of hidden layers in the Transformer encoder.

  • num_attention_heads (int, optional, defaults to 32) – Number of attention heads for each attention layer in the Transformer encoder.

  • num_key_value_heads (int, optional) – Number of key and value heads for each attention layer in the Transformer encoder. Will default to num_attention_heads if not set.

  • resid_pdrop (float, optional, defaults to 0.0) – The dropout probability for all fully connected layers in the embeddings, encoder, and pooler.

  • embd_pdrop (float, optional, defaults to 0.0) – The dropout ratio for the embeddings.

  • attention_dropout (float, optional, defaults to 0.0) – The dropout ratio for the attention probabilities.

  • hidden_act (str or function, optional, defaults to “silu”) – The non-linear activation function (function or string) to use in the encoder and pooler. If string, “gelu”, “relu”, “swish” and “gelu_new” are supported.

  • max_position_embeddings (int, optional, defaults to 4096) – The maximum sequence length that this model might ever be used with. Typically set this to something large just in case (e.g., 2048 or 4096).

  • original_max_position_embeddings (int, optional, defaults to 4096) – The original maximum sequence length that this model might ever be used with. Typically set this to something large just in case (e.g., 2048 or 4096).

  • initializer_range (float, optional, defaults to 0.02) – The standard deviation of the truncated_normal_initializer for initializing all weight matrices.

  • rms_norm_eps (float, optional, defaults to 1e-5) – The epsilon used by the rms normalization layers.

  • use_cache (bool, optional, defaults to True) – Whether or not the model should return the last key/values attentions (not used by all models). Only relevant if config.is_decoder=True.

  • tie_word_embeddings (bool, optional, defaults to False) – Whether to tie the weights of the input embeddings and the output embeddings.

  • rope_theta (float, optional, defaults to 10000.0) – The theta value to use for rotary position embeddings.

  • rope_scaling (tp.Dict[str, tp.Union[str, float]], optional) – The configuration for rope scaling.

  • bos_token_id (int, optional, defaults to 1) – The id of the beginning-of-sequence token.

  • eos_token_id (int, optional, defaults to 32000) – The id of the end-of-sequence token.

  • pad_token_id (int, optional, defaults to 32000) – The index of the padding token in the vocabulary.

  • sliding_window (int, optional) – The sliding window size.

  • bits (int, optional) – The number of bits to quantize the model to.

  • gradient_checkpointing (str, optional, defaults to “nothing_saveable”) – The gradient checkpointing configuration.

get_partition_rules(*args, **kwargs)[source]#

Get the partition rules for the model.

Returns

The partition rules.

Return type

tp.Tuple[tp.Tuple[str, PartitionSpec]]

property granted_freq_max_position_embedding: int#
property granted_mask_max_position_embedding: int#
model_type: str = 'phi3'#
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