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Create configuration_falcon.py

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configuration_falcon.py ADDED
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+ # coding=utf-8
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+ # Copyright 2023 the Falcon authors and HuggingFace Inc. team. All rights reserved.
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+ """ Falcon configuration"""
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+ from transformers.configuration_utils import PretrainedConfig
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+ from transformers.utils import logging
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+
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+
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+ logger = logging.get_logger(__name__)
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+
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+ FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP = {
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+ "tiiuae/falcon-40b": "https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json",
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+ "tiiuae/falcon-7b": "https://huggingface.co/tiiuae/falcon-7b/resolve/main/config.json",
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+ }
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+
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+
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+ class FalconConfig(PretrainedConfig):
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+ r"""
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+ This is the configuration class to store the configuration of a [`FalconModel`]. It is used to instantiate a Falcon
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+ model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
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+ defaults will yield a similar configuration to that of the
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+ [tiiuae/falcon-7b](https://huggingface.co/tiiuae/falcon-7b) architecture.
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+
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+ Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
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+ documentation from [`PretrainedConfig`] for more information.
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+
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+
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+ Args:
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+ vocab_size (`int`, *optional*, defaults to 65024):
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+ Vocabulary size of the Falcon model. Defines the number of different tokens that can be represented by the
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+ `inputs_ids` passed when calling [`FalconModel`]
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+ hidden_size (`int`, *optional*, defaults to 4544):
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+ Dimension of the hidden representations.
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+ num_hidden_layers (`int`, *optional*, defaults to 32):
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+ Number of hidden layers in the Transformer decoder.
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+ num_attention_heads (`int`, *optional*, defaults to 71):
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+ Number of attention heads for each attention layer in the Transformer encoder.
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+ initializer_range (`float`, *optional*, defaults to 0.02):
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+ The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
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+ use_cache (`bool`, *optional*, defaults to `True`):
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+ Whether the model should return the last key/values attentions (not used by all models). Only relevant if
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+ `config.is_decoder=True`.
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+ layer_norm_epsilon (`float`, *optional*, defaults to 1e-5):
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+ The epsilon used by the layer normalization layers.
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+ hidden_dropout (`float`, *optional*, defaults to 0.0):
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+ The dropout probability for MLP layers.
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+ attention_dropout (`float`, *optional*, defaults to 0.0):
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+ The dropout probability for attention layers.
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+ num_kv_heads (`int`, *optional*):
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+ Number of key-value heads to use per attention layer. If unset, defaults to the same value as
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+ `num_attention_heads`.
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+ alibi (`bool`, *optional*, defaults to `False`):
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+ Whether to use ALiBi positional biases during self-attention.
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+ new_decoder_architecture (`bool`, *optional*, defaults to `False`):
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+ Whether to use the new (Falcon-40B) decoder architecture. If `True`, the `multi_query` and `parallel_attn`
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+ arguments are ignored, as the new decoder always uses parallel attention.
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+ multi_query (`bool`, *optional*, defaults to `True`):
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+ Whether to use multi-query attention in the decoder. Ignored when `new_decoder_architecture` is `True`.
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+ parallel_attn (`bool`, *optional*, defaults to `True`):
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+ Whether to compute attention in parallel with the feedforward layer. If False, they are consecutive
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+ instead, as in the original Transformer architecture. Ignored when `new_decoder_architecture` is `True`.
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+ bias (`bool`, *optional*, defaults to `False`):
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+ Whether to use bias on Linear layers.
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+ bos_token_id (`int`, *optional*, defaults to 11):
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+ The id of the "beginning-of-sequence" token.
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+ eos_token_id (`int`, *optional*, defaults to 11):
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+ The id of the "end-of-sequence" token.
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+
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+ Example:
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+
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+ ```python
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+ >>> from transformers import FalconModel, FalconConfig
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+
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+ >>> # Initializing a small (2-layer) Falcon configuration
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+ >>> configuration = FalconConfig(num_hidden_layers=2)
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+
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+ >>> # Initializing a model from the small configuration
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+ >>> model = FalconModel(configuration)
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+
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+ >>> # Accessing the model configuration
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+ >>> configuration = model.config
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+ ```"""
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+ model_type = "falcon"
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+ keys_to_ignore_at_inference = ["past_key_values"]
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+
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+ def __init__(
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+ self,
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+ vocab_size=65024,
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+ hidden_size=4544,
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+ num_hidden_layers=32,
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+ num_attention_heads=71,
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+ layer_norm_epsilon=1e-5,
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+ initializer_range=0.02,
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+ use_cache=True,
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+ hidden_dropout=0.0,
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+ attention_dropout=0.0,
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+ num_kv_heads=None,
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+ alibi=False,
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+ new_decoder_architecture=False,
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+ multi_query=True,
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+ parallel_attn=True,
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+ bias=False,
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+ bos_token_id=11,
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+ eos_token_id=11,
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+ **kwargs,
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+ ):
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+ self.vocab_size = vocab_size
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+ # Backward compatibility with n_embed kwarg
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+ n_embed = kwargs.pop("n_embed", None)
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+ self.hidden_size = hidden_size if n_embed is None else n_embed
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+ self.num_hidden_layers = num_hidden_layers
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+ self.num_attention_heads = num_attention_heads
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+ self.layer_norm_epsilon = layer_norm_epsilon
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+ self.initializer_range = initializer_range
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+ self.use_cache = use_cache
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+ self.hidden_dropout = hidden_dropout
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+ self.attention_dropout = attention_dropout
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+
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+ self.bos_token_id = bos_token_id
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+ self.eos_token_id = eos_token_id
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+ self.num_kv_heads = num_attention_heads if num_kv_heads is None else num_kv_heads
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+ self.alibi = alibi
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+ self.new_decoder_architecture = new_decoder_architecture
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+ self.multi_query = multi_query # Ignored when new_decoder_architecture is True
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+ self.parallel_attn = parallel_attn
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+ self.bias = bias
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+
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+ super().__init__(bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
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+
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+ @property
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+ def head_dim(self):
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+ return self.hidden_size // self.num_attention_heads
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+
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+ @property
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+ def rotary(self):
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+ return not self.alibi