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Functions1,559 in github.com/adapter-hub/adapters

⨍ Functions 1,559◇ Types & classes 451↳ Endpoints 1

Method__getattr__

examples/pytorch/text-generation/run_generation.py:264

Method__getitem__

src/adapters/composition.py:14

Method__getitem__

src/adapters/configuration/adapter_config.py:37

Method__getitem__

src/adapters/configuration/adapter_config.py:816

Method__getitem__

src/adapters/heads/base.py:37

(self, adapter_setup, head_setup=None, ignore_empty: bool = False)

src/adapters/context.py:27

(self, model, *args, **kwargs)

src/adapters/context.py:96

(self, *children)

src/adapters/composition.py:11

Can be used to perform inference for multiple tasks (i.e., adapters) in parallel (for the same input). See AdapterDrop https://arxiv

src/adapters/composition.py:76

(self, *stack_layers: List[Union[AdapterCompositionBlock, str]])

src/adapters/composition.py:90

( self, *split_adapters: List[Union[AdapterCompositionBlock, str]], splits: Union[List

src/adapters/composition.py:113

( self, *split_adapters: List[Union[AdapterCompositionBlock, str]], batch_sizes: Union

src/adapters/composition.py:126

(self, *children)

src/adapters/composition.py:139

( self, *average_adapters: List[Union[AdapterCompositionBlock, str]], weights: Optiona

src/adapters/composition.py:144

( self, model, weights_name, config_name, use_safetensors: bool = Fals

src/adapters/loading.py:45

(self, model, adapter_type=None, use_safetensors: bool = False)

src/adapters/loading.py:371

(self, model, error_on_missing=True, use_safetensors: bool = False)

src/adapters/loading.py:663

( self, model, error_on_missing=True, convert_to_flex_head=False, use_

src/adapters/loading.py:840

(self, config, *args, **kwargs)

src/adapters/model_mixin.py:2104

(self, trainer)

src/adapters/trainer.py:247

(self, **kwargs)

src/adapters/configuration/model_adapters_config.py:19

src/adapters/configuration/adapter_config.py:23

(self, *configs: List[AdapterConfig])

src/adapters/configuration/adapter_config.py:777

( self, prefix_tuning: Optional[PrefixTuningConfig] = None, adapter: Optional[BnConfig

src/adapters/configuration/adapter_config.py:889

( self, model_config: PretrainedConfig, adapters_config: ModelAdaptersConfig,

src/adapters/methods/prompt_tuning.py:148

(self, *args, **kwargs)

src/adapters/methods/adapter_layer_base.py:233

(self, hidden_act)

src/adapters/methods/modeling.py:19

(self, adapter_name, input_size, down_sample, config: BnConfig)

src/adapters/methods/modeling.py:282

( self, config: AdapterFusionConfig, dense_size, attention_probs_dropout_prob,

src/adapters/methods/modeling.py:364

(self, dims_in, dims_c=[], non_linearity="relu", reduction_factor=2)

src/adapters/methods/modeling.py:476

(self, dims_in, dims_c=[], non_linearity="relu", reduction_factor=2, clamp=5.0)

src/adapters/methods/modeling.py:524

( self, adapter_name: str, in_features: int, out_features: int, positi

src/adapters/methods/modeling.py:606

( self, n_layers: int, n_heads: int, input_size: int, config: PrefixTu

src/adapters/methods/prefix_tuning.py:78

(self, module_configs, prefix_tuning_config)

src/adapters/methods/prefix_tuning.py:123

( self, model_config: PretrainedConfig, adapters_config: ModelAdaptersConfig, )

src/adapters/methods/prefix_tuning.py:167

( self, location_key: str, model_config: PretrainedConfig, adapters_config: Mo

src/adapters/methods/prefix_tuning.py:332

(self, model_config, adapters_config)

src/adapters/methods/invertible.py:16

(self, in_features: int, config: ReftConfig)

src/adapters/methods/reft.py:66

(self, location_key: str, model_config, adapters_config)

src/adapters/methods/reft.py:187

(self, location_key: str, is_layer_hooked: bool = False)

src/adapters/methods/bottleneck.py:55

(self, rank: int, dtype: Optional[str] = None)

src/adapters/methods/lora.py:38

(self, rank: int, dtype: Optional[str] = None)

src/adapters/methods/lora.py:49

( self, lora_A_shape, lora_B_shape, config: LoRAConfig, gating_heads:

src/adapters/methods/lora.py:70

( self, lora_A_shape, lora_B_shape, config: MTLLoRAConfig, gating_head

src/adapters/methods/lora.py:178

( self, lora_A_shape, lora_B_shape, config: LoRAConfig, gating_heads:

src/adapters/methods/lora.py:317

( self, location_key: str, model_config: PretrainedConfig, adapters_config: Mo

src/adapters/methods/lora.py:509

( self, in_features: int, out_features: int, location_key: str, model_

src/adapters/methods/lora.py:775

( self, in_features: int, out_features: int, location_key: str, model_

src/adapters/methods/lora.py:1077

(self, model, head_name, num_labels=2, id2label=None)

src/adapters/heads/dependency_parsing.py:69

src/adapters/heads/base.py:63

( self, model, head_name, num_labels=2, layers=2, activation_f

src/adapters/heads/base.py:134

( self, model, head_name, num_labels=2, layers=2, activation_f

src/adapters/heads/base.py:202

( self, model, head_name, num_choices=2, layers=2, activation_

src/adapters/heads/base.py:267

( self, model, head_name, num_labels=2, layers=1, activation_f

src/adapters/heads/base.py:383

( self, model, head_name, num_labels=2, layers=2, activation_f

src/adapters/heads/base.py:465

(self, *args, **kwargs)

src/adapters/heads/model_mixin.py:52

( self, model, head_name, vocab_size=None, layers=1, activatio

src/adapters/heads/language_modeling.py:146

( self, model, head_name, vocab_size=None, embedding_size=None,

src/adapters/heads/language_modeling.py:186

src/adapters/models/beit/adapter_model.py:23

src/adapters/models/roberta/adapter_model.py:29

src/adapters/models/albert/adapter_model.py:25

src/adapters/models/llama/adapter_model.py:42

(self, config: PLBartConfig, **kwargs)

src/adapters/models/plbart/adapter_model.py:37

(self, config: BartConfig, **kwargs)

src/adapters/models/bart/adapter_model.py:32

src/adapters/models/mistral/adapter_model.py:41

src/adapters/models/xmod/adapter_model.py:34

src/adapters/models/vit/adapter_model.py:23

src/adapters/models/deberta/adapter_model.py:28

src/adapters/models/clip/adapter_model.py:19

src/adapters/models/deberta_v2/adapter_model.py:28

src/adapters/models/bert/adapter_model.py:33

src/adapters/models/bert/mixin_bert.py:36

(self, config: WhisperConfig, **kwargs)

src/adapters/models/whisper/adapter_model.py:29

src/adapters/models/xlm_roberta/adapter_model.py:30

src/adapters/models/bert_generation/adapter_model.py:28

src/adapters/models/distilbert/adapter_model.py:31

src/adapters/models/gptj/adapter_model.py:41

src/adapters/models/gpt2/adapter_model.py:43

src/adapters/models/electra/adapter_model.py:30

(self, config: MBartConfig, **kwargs)

src/adapters/models/mbart/adapter_model.py:33

src/adapters/models/mt5/adapter_model.py:42

src/adapters/models/t5/mixin_t5.py:35

src/adapters/models/t5/mixin_t5.py:45

src/adapters/models/t5/adapter_model.py:42

( self, model, head_name, **config, )

tests/test_misc/test_adapter_custom_head.py:14

(self, embed_dim=32, depth=4, num_heads=4, mlp_ratio=2, img_size=(64, 128), patch_size=16, **kwargs)

tests/test_methods/test_all_custom_interfaces.py:39

(self, dim, num_heads)

tests/test_methods/test_all_custom_interfaces.py:50

(self, dim, num_heads, mlp_ratio)

tests/test_methods/test_all_custom_interfaces.py:78

tests/test_methods/test_all_custom_interfaces.py:94

tests/test_methods/test_all_custom_interfaces.py:118

( self, model: Union[PreTrainedModel, torch.nn.Module] = None, args: UDTrainingArgumen

examples/pytorch/dependency-parsing/utils_udp.py:175

(self, optimized, default)

examples/pytorch/text-generation/run_generation.py:241

(self, *args, eval_examples=None, post_process_function=None, **kwargs)

examples/pytorch/question-answering/trainer_seq2seq_qa.py:30

(self, *args, eval_examples=None, post_process_function=None, **kwargs)

examples/pytorch/question-answering/trainer_qa.py:27

src/adapters/configuration/model_adapters_config.py:41

src/adapters/configuration/adapter_config.py:40

src/adapters/configuration/adapter_config.py:825

src/adapters/heads/base.py:53

src/adapters/composition.py:17

src/adapters/configuration/model_adapters_config.py:44

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