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EXAONE-Deep-7.8B-int4_asym-gptq-se-ov

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  1. config.json +39 -0
  2. configuration_exaone.py +182 -0
  3. generation_config.json +10 -0
  4. merges.txt +0 -0
  5. openvino_config.json +27 -0
  6. openvino_detokenizer.bin +3 -0
  7. openvino_detokenizer.xml +337 -0
  8. openvino_model.bin +3 -0
  9. openvino_model.xml +0 -0
  10. openvino_tokenizer.bin +3 -0
  11. openvino_tokenizer.xml +798 -0
  12. special_tokens_map.json +30 -0
  13. tokenizer.json +0 -0
  14. tokenizer_config.json +3222 -0
  15. vocab.json +0 -0
config.json ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "activation_function": "silu",
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+ "architectures": [
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+ "ExaoneForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "auto_map": {
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+ "AutoConfig": "configuration_exaone.ExaoneConfig",
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+ "AutoModelForCausalLM": "modeling_exaone.ExaoneForCausalLM",
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+ "AutoModelForSequenceClassification": "modeling_exaone.ExaoneForSequenceClassification"
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+ },
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+ "bos_token_id": 1,
13
+ "embed_dropout": 0.0,
14
+ "eos_token_id": 361,
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+ "head_dim": 128,
16
+ "hidden_size": 4096,
17
+ "initializer_range": 0.02,
18
+ "intermediate_size": 14336,
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+ "layer_norm_epsilon": 1e-05,
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+ "max_position_embeddings": 32768,
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+ "model_type": "exaone",
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+ "num_attention_heads": 32,
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+ "num_key_value_heads": 8,
24
+ "num_layers": 32,
25
+ "pad_token_id": 0,
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+ "rope_scaling": {
27
+ "factor": 8.0,
28
+ "high_freq_factor": 4.0,
29
+ "low_freq_factor": 1.0,
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+ "original_max_position_embeddings": 8192,
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+ "rope_type": "llama3"
32
+ },
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+ "rope_theta": 1000000.0,
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+ "tie_word_embeddings": false,
35
+ "torch_dtype": "bfloat16",
36
+ "transformers_version": "4.50.2",
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+ "use_cache": true,
38
+ "vocab_size": 102400
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+ }
configuration_exaone.py ADDED
@@ -0,0 +1,182 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # coding=utf-8
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+ # Copyright 2021 The LG AI Research EXAONE Lab. 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.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
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+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+ """EXAONE model configuration"""
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+
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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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+ EXAONE_PRETRAINED_CONFIG_ARCHIVE_MAP = {}
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+
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+
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+ class ExaoneConfig(PretrainedConfig):
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+ r"""
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+ This is the configuration class to store the configuration of a [`ExaoneModel`]. It is used to
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+ instantiate a EXAONE model according to the specified arguments, defining the model architecture. Instantiating a
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+ configuration with the defaults will yield a similar configuration to that of the EXAONE-3.0-7.8B-Instruct [LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct)
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+
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+ Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model
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+ outputs. Read the 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 102400):
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+ Vocabulary size of the EXAONE model. Defines the number of different tokens that can be represented by the
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+ `inputs_ids` passed when calling [`ExaoneModel`]. Vocabulary size of the model.
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+ Defines the different tokens that can be represented by the `inputs_ids` passed to the forward method of
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+ [`ExaoneModel`].
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+ max_position_embeddings (`int`, *optional*, defaults to 2048):
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+ The maximum sequence length that this model might ever be used with. Typically set this to something large
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+ just in case (e.g., 512 or 1024 or 2048).
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+ hidden_size (`int`, *optional*, defaults to 2048):
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+ Dimensionality of the encoder layers and the pooler layer.
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+ num_layers (`int`, *optional*, defaults to 32):
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+ Number of hidden layers in the Transformer encoder.
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+ num_attention_heads (`int`, *optional*, defaults to 32):
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+ Number of attention heads for each attention layer in the Transformer decoder.
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+ num_key_value_heads (`int`, *optional*):
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+ This is the number of key_value heads that should be used to implement Grouped Query Attention. If
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+ `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
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+ `num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
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+ converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
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+ by meanpooling all the original heads within that group. For more details checkout [this
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+ paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
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+ `num_attention_heads`.
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+ intermediate_size (`int`, *optional*, defaults to `hidden_size * 4`):
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+ Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder.
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+ activation_function (`str` or `function`, *optional*, defaults to `"silu"`):
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+ The non-linear activation function (function or string) in the decoder.
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+ rope_theta (`float`, *optional*, defaults to 10000.0):
64
+ The base period of the RoPE embeddings.
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+ rope_scaling (`Dict`, *optional*):
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+ Dictionary containing the scaling configuration for the RoPE embeddings. NOTE: if you apply new rope type
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+ and you expect the model to work on longer `max_position_embeddings`, we recommend you to update this value
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+ accordingly.
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+ Expected contents:
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+ `rope_type` (`str`):
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+ The sub-variant of RoPE to use. Can be one of ['default', 'linear', 'dynamic', 'yarn', 'longrope',
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+ 'llama3'], with 'default' being the original RoPE implementation.
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+ `factor` (`float`, *optional*):
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+ Used with all rope types except 'default'. The scaling factor to apply to the RoPE embeddings. In
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+ most scaling types, a `factor` of x will enable the model to handle sequences of length x *
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+ original maximum pre-trained length.
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+ `original_max_position_embeddings` (`int`, *optional*):
78
+ Used with 'dynamic', 'longrope' and 'llama3'. The original max position embeddings used during
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+ pretraining.
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+ `attention_factor` (`float`, *optional*):
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+ Used with 'yarn' and 'longrope'. The scaling factor to be applied on the attention
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+ computation. If unspecified, it defaults to value recommended by the implementation, using the
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+ `factor` field to infer the suggested value.
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+ `beta_fast` (`float`, *optional*):
85
+ Only used with 'yarn'. Parameter to set the boundary for extrapolation (only) in the linear
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+ ramp function. If unspecified, it defaults to 32.
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+ `beta_slow` (`float`, *optional*):
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+ Only used with 'yarn'. Parameter to set the boundary for interpolation (only) in the linear
89
+ ramp function. If unspecified, it defaults to 1.
90
+ `short_factor` (`List[float]`, *optional*):
91
+ Only used with 'longrope'. The scaling factor to be applied to short contexts (<
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+ `original_max_position_embeddings`). Must be a list of numbers with the same length as the hidden
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+ size divided by the number of attention heads divided by 2
94
+ `long_factor` (`List[float]`, *optional*):
95
+ Only used with 'longrope'. The scaling factor to be applied to long contexts (<
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+ `original_max_position_embeddings`). Must be a list of numbers with the same length as the hidden
97
+ size divided by the number of attention heads divided by 2
98
+ `low_freq_factor` (`float`, *optional*):
99
+ Only used with 'llama3'. Scaling factor applied to low frequency components of the RoPE
100
+ `high_freq_factor` (`float`, *optional*):
101
+ Only used with 'llama3'. Scaling factor applied to high frequency components of the RoPE
102
+ embed_dropout (`float`, *optional*, defaults to 0.0):
103
+ The dropout probabilitiy for all fully connected layers in the embeddings, encoder, and pooler.
104
+ attention_dropout (`float`, *optional*, defaults to 0.0):
105
+ The dropout ratio for the attention probabilities.
106
+ layer_norm_epsilon (`float`, *optional*, defaults to 1e-05):
107
+ The epsilon used by the layer normalization layers.
108
+ initializer_range (`float`, *optional*, defaults to 0.02):
109
+ The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
110
+ use_cache (`bool`, *optional*, defaults to `True`):
111
+ Whether or not the model should return the last key/values attentions (not used by all models). Only
112
+ relevant if ``config.is_decoder=True``.
113
+ bos_token_id (`int`, *optional*, defaults to 0):
114
+ Beginning of stream token id.
115
+ eos_token_id (`int`, *optional*, defaults to 2):
116
+ End of stream token id.
117
+
118
+ Example:
119
+
120
+ ```python
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+ >>> from transformers import EXAONEModel, ExaoneConfig
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+
123
+ >>> # Initializing a EXAONE configuration
124
+ >>> configuration = ExaoneConfig()
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+
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+ >>> # Initializing a model from configuration
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+ >>> model = EXAONEModel(configuration)
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+
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+ >>> # Accessing the model configuration
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+ >>> configuration = model.config
131
+ ```"""
132
+
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+ model_type = "exaone"
134
+ keys_to_ignore_at_inference = ["past_key_values"]
135
+ attribute_map = {"num_hidden_layers": "num_layers"}
136
+
137
+ def __init__(
138
+ self,
139
+ vocab_size=102400,
140
+ max_position_embeddings=2048,
141
+ hidden_size=2048,
142
+ num_layers=32,
143
+ num_attention_heads=32,
144
+ num_key_value_heads=None,
145
+ intermediate_size=None,
146
+ activation_function="silu",
147
+ rope_theta=10000.0,
148
+ rope_scaling=None,
149
+ embed_dropout=0.0,
150
+ attention_dropout=0.0,
151
+ layer_norm_epsilon=1e-5,
152
+ initializer_range=0.02,
153
+ use_cache=True,
154
+ bos_token_id=0,
155
+ eos_token_id=2,
156
+ **kwargs,
157
+ ):
158
+ self.vocab_size = vocab_size
159
+ self.max_position_embeddings = max_position_embeddings
160
+ self.hidden_size = hidden_size
161
+ self.num_layers = num_layers
162
+ self.num_attention_heads = num_attention_heads
163
+ if num_key_value_heads is None:
164
+ num_key_value_heads = num_attention_heads
165
+ self.num_key_value_heads = num_key_value_heads
166
+ if intermediate_size:
167
+ self.intermediate_size = intermediate_size
168
+ else:
169
+ self.intermediate_size = hidden_size * 4
170
+ self.activation_function = activation_function
171
+ self.embed_dropout = embed_dropout
172
+ self.attention_dropout = attention_dropout
173
+ self.layer_norm_epsilon = layer_norm_epsilon
174
+ self.initializer_range = initializer_range
175
+ self.use_cache = use_cache
176
+ self.rope_theta = rope_theta
177
+ self.rope_scaling = rope_scaling
178
+
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+ self.bos_token_id = bos_token_id
180
+ self.eos_token_id = eos_token_id
181
+
182
+ super().__init__(bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
generation_config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "_from_model_config": true,
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+ "eos_token_id": 361,
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+ "pad_token_id": 0,
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+ "temperature": 0.6,
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+ "top_p": 0.95,
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+ "transformers_version": "4.50.2"
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+ }
merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
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+ "[extra_id_57]",
3060
+ "[extra_id_58]",
3061
+ "[extra_id_59]",
3062
+ "[extra_id_60]",
3063
+ "[extra_id_61]",
3064
+ "[extra_id_62]",
3065
+ "[extra_id_63]",
3066
+ "[extra_id_64]",
3067
+ "[extra_id_65]",
3068
+ "[extra_id_66]",
3069
+ "[extra_id_67]",
3070
+ "[extra_id_68]",
3071
+ "[extra_id_69]",
3072
+ "[extra_id_70]",
3073
+ "[extra_id_71]",
3074
+ "[extra_id_72]",
3075
+ "[extra_id_73]",
3076
+ "[extra_id_74]",
3077
+ "[extra_id_75]",
3078
+ "[extra_id_76]",
3079
+ "[extra_id_77]",
3080
+ "[extra_id_78]",
3081
+ "[extra_id_79]",
3082
+ "[extra_id_80]",
3083
+ "[extra_id_81]",
3084
+ "[extra_id_82]",
3085
+ "[extra_id_83]",
3086
+ "[extra_id_84]",
3087
+ "[extra_id_85]",
3088
+ "[extra_id_86]",
3089
+ "[extra_id_87]",
3090
+ "[extra_id_88]",
3091
+ "[extra_id_89]",
3092
+ "[extra_id_90]",
3093
+ "[extra_id_91]",
3094
+ "[extra_id_92]",
3095
+ "[extra_id_93]",
3096
+ "[extra_id_94]",
3097
+ "[extra_id_95]",
3098
+ "[extra_id_96]",
3099
+ "[extra_id_97]",
3100
+ "[extra_id_98]",
3101
+ "[extra_id_99]",
3102
+ "[extra_id_100]",
3103
+ "[extra_id_101]",
3104
+ "[extra_id_102]",
3105
+ "[extra_id_103]",
3106
+ "[extra_id_104]",
3107
+ "[extra_id_105]",
3108
+ "[extra_id_106]",
3109
+ "[extra_id_107]",
3110
+ "[extra_id_108]",
3111
+ "[extra_id_109]",
3112
+ "[extra_id_110]",
3113
+ "[extra_id_111]",
3114
+ "[extra_id_112]",
3115
+ "[extra_id_113]",
3116
+ "[extra_id_114]",
3117
+ "[extra_id_115]",
3118
+ "[extra_id_116]",
3119
+ "[extra_id_117]",
3120
+ "[extra_id_118]",
3121
+ "[extra_id_119]",
3122
+ "[extra_id_120]",
3123
+ "[extra_id_121]",
3124
+ "[extra_id_122]",
3125
+ "[extra_id_123]",
3126
+ "[extra_id_124]",
3127
+ "[extra_id_125]",
3128
+ "[extra_id_126]",
3129
+ "[extra_id_127]",
3130
+ "[extra_id_128]",
3131
+ "[extra_id_129]",
3132
+ "[extra_id_130]",
3133
+ "[extra_id_131]",
3134
+ "[extra_id_132]",
3135
+ "[extra_id_133]",
3136
+ "[extra_id_134]",
3137
+ "[extra_id_135]",
3138
+ "[extra_id_136]",
3139
+ "[extra_id_137]",
3140
+ "[extra_id_138]",
3141
+ "[extra_id_139]",
3142
+ "[extra_id_140]",
3143
+ "[extra_id_141]",
3144
+ "[extra_id_142]",
3145
+ "[extra_id_143]",
3146
+ "[extra_id_144]",
3147
+ "[extra_id_145]",
3148
+ "[extra_id_146]",
3149
+ "[extra_id_147]",
3150
+ "[extra_id_148]",
3151
+ "[extra_id_149]",
3152
+ "[extra_id_150]",
3153
+ "[extra_id_151]",
3154
+ "[extra_id_152]",
3155
+ "[extra_id_153]",
3156
+ "[extra_id_154]",
3157
+ "[extra_id_155]",
3158
+ "[extra_id_156]",
3159
+ "[extra_id_157]",
3160
+ "[extra_id_158]",
3161
+ "[extra_id_159]",
3162
+ "[extra_id_160]",
3163
+ "[extra_id_161]",
3164
+ "[extra_id_162]",
3165
+ "[extra_id_163]",
3166
+ "[extra_id_164]",
3167
+ "[extra_id_165]",
3168
+ "[extra_id_166]",
3169
+ "[extra_id_167]",
3170
+ "[extra_id_168]",
3171
+ "[extra_id_169]",
3172
+ "[extra_id_170]",
3173
+ "[extra_id_171]",
3174
+ "[extra_id_172]",
3175
+ "[extra_id_173]",
3176
+ "[extra_id_174]",
3177
+ "[extra_id_175]",
3178
+ "[extra_id_176]",
3179
+ "[extra_id_177]",
3180
+ "[extra_id_178]",
3181
+ "[extra_id_179]",
3182
+ "[extra_id_180]",
3183
+ "[extra_id_181]",
3184
+ "[extra_id_182]",
3185
+ "[extra_id_183]",
3186
+ "[extra_id_184]",
3187
+ "[extra_id_185]",
3188
+ "[extra_id_186]",
3189
+ "[extra_id_187]",
3190
+ "[extra_id_188]",
3191
+ "[extra_id_189]",
3192
+ "[extra_id_190]",
3193
+ "[extra_id_191]",
3194
+ "[extra_id_192]",
3195
+ "[extra_id_193]",
3196
+ "[extra_id_194]",
3197
+ "[extra_id_195]",
3198
+ "[extra_id_196]",
3199
+ "[extra_id_197]",
3200
+ "[extra_id_198]",
3201
+ "[|endofturn|]",
3202
+ "PI:URL",
3203
+ "PI:EMAIL",
3204
+ "PI:ACCOUNT_NUM",
3205
+ "PI:PHONE_NUM",
3206
+ "PI:BUSINESS_NUM",
3207
+ "PI:ANNON",
3208
+ "PI:KEY",
3209
+ "PI:ID",
3210
+ "PI:IP_ADDRESS",
3211
+ "PI:USER"
3212
+ ],
3213
+ "bos_token": "[BOS]",
3214
+ "chat_template": "{% for message in messages %}{% if loop.first and message['role'] != 'system' %}{{ '[|system|][|endofturn|]\n' }}{% endif %}{% set content = message['content'] %}{% if '</thought>' in content %}{% set content = content.split('</thought>')[-1].lstrip('\\n') %}{% endif %}{{ '[|' + message['role'] + '|]' + content }}{% if not message['role'] == 'user' %}{{ '[|endofturn|]' }}{% endif %}{% if not loop.last %}{{ '\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '\n[|assistant|]<thought>\n' }}{% endif %}",
3215
+ "clean_up_tokenization_spaces": true,
3216
+ "eos_token": "[|endofturn|]",
3217
+ "extra_special_tokens": {},
3218
+ "model_max_length": 1000000000000000019884624838656,
3219
+ "pad_token": "[PAD]",
3220
+ "tokenizer_class": "GPT2Tokenizer",
3221
+ "unk_token": "[UNK]"
3222
+ }
vocab.json ADDED
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