Datasets:
itazap
/
transformers_code_embeddings_v3

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1
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24
102
embedding
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2.56k
2.56k
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4
448
owlv2/modeling_owlv2.py:Owlv2TextEmbeddings
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[ "Embedding", "False", "ModelTextEmbeddings", "Module", "None", "__init__", "arange", "class", "config", "def", "else", "embeddings", "expand", "forward", "hidden_size", "if", "input_ids", "inputs_embeds", "is", "max_position_embeddings", "nn", "not", "persistent", "posi...
owlv2/modeling_owlv2.py:Owlv2Attention
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[ "Attention", "False", "Linear", "ModelAttention", "Module", "None", "ValueError", "__init__", "_shape", "and", "attention_dropout", "attention_mask", "attn_output", "attn_probs", "attn_weights", "attn_weights_reshaped", "be", "bmm", "bsz", "but", "by", "causal_attention_mas...
owlv2/modeling_owlv2.py:Owlv2MLP
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[ "ACT2FN", "Linear", "ModelMLP", "Module", "__init__", "activation_fn", "class", "config", "def", "fc1", "fc2", "forward", "hidden_act", "hidden_size", "hidden_states", "intermediate_size", "nn", "return", "self", "super" ]
owlv2/modeling_owlv2.py:Owlv2EncoderLayer
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[ "False", "GradientCheckpointingLayer", "LayerNorm", "ModelAttention", "ModelEncoderLayer", "ModelMLP", "__init__", "attention_mask", "attn_weights", "causal_attention_mask", "class", "config", "def", "embed_dim", "eps", "forward", "hidden_size", "hidden_states", "if", "layer_no...
owlv2/modeling_owlv2.py:Owlv2PreTrainedModel
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[ "LayerNorm", "Linear", "Model", "ModelAttention", "ModelConfig", "ModelEncoderLayer", "ModelForObjectDetection", "ModelMLP", "ModelModel", "ModelPreTrainedModel", "ModelTextEmbeddings", "ModelVisionEmbeddings", "None", "PreTrainedModel", "True", "_init_weights", "_no_split_modules", ...
owlv2/modeling_owlv2.py:Owlv2Encoder
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[ "BaseModelOutput", "False", "ModelEncoder", "ModelEncoderLayer", "Module", "ModuleList", "None", "_", "__init__", "all_attentions", "attention_mask", "attentions", "causal_attention_mask", "class", "config", "def", "else", "encoder_layer", "encoder_states", "for", "forward", ...
owlv2/modeling_owlv2.py:Owlv2TextTransformer
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[ "BaseModelOutputWithPooling", "LayerNorm", "ModelEncoder", "ModelTextEmbeddings", "ModelTextTransformer", "Module", "None", "__init__", "_create_4d_causal_attention_mask", "_prepare_4d_attention_mask", "arange", "argmax", "attention_mask", "attentions", "auto_docstring", "causal_attent...
owlv2/modeling_owlv2.py:Owlv2TextModel
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[ "ModelPreTrainedModel", "ModelTextConfig", "ModelTextModel", "ModelTextTransformer", "None", "__init__", "attention_mask", "auto_docstring", "class", "config", "def", "embeddings", "forward", "get_input_embeddings", "input_ids", "input_modalities", "kwargs", "output_attentions", ...
owlv2/modeling_owlv2.py:Owlv2VisionTransformer
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[ "BaseModelOutputWithPooling", "False", "LayerNorm", "ModelEncoder", "ModelVisionEmbeddings", "ModelVisionTransformer", "Module", "None", "__init__", "attentions", "auto_docstring", "class", "config", "def", "dtype", "else", "embeddings", "encoder", "encoder_outputs", "eps", "...
owlv2/modeling_owlv2.py:Owlv2VisionModel
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[ "False", "ModelPreTrainedModel", "ModelVisionConfig", "ModelVisionModel", "ModelVisionTransformer", "None", "__init__", "auto_docstring", "class", "config", "def", "embeddings", "forward", "get_input_embeddings", "image", "input_modalities", "interpolate_pos_encoding", "kwargs", ...
owlv2/modeling_owlv2.py:Owlv2Model
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[ "False", "Linear", "ModelConfig", "ModelModel", "ModelOutput", "ModelPreTrainedModel", "ModelTextConfig", "ModelTextTransformer", "ModelVisionConfig", "ModelVisionTransformer", "Model_loss", "None", "Parameter", "True", "TypeError", "__init__", "attention_mask", "auto_docstring", ...
owlv2/modeling_owlv2.py:Owlv2BoxPredictionHead
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[ "GELU", "Linear", "ModelBoxPredictionHead", "Module", "__init__", "class", "config", "def", "dense0", "dense1", "dense2", "forward", "gelu", "hidden_size", "image_features", "nn", "out_dim", "output", "return", "self", "super", "vision_config", "width" ]
owlv2/modeling_owlv2.py:Owlv2ClassPredictionHead
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[ "ELU", "Linear", "ModelClassPredictionHead", "Module", "None", "True", "__init__", "batch_size", "class", "config", "def", "dense0", "device", "dim", "dtype", "einsum", "elu", "finfo", "float32", "forward", "hidden_size", "if", "image_class_embeds", "image_embeds", "i...
owlv2/modeling_owlv2.py:Owlv2ForObjectDetection
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[ "False", "LayerNorm", "Model", "ModelBoxPredictionHead", "ModelClassPredictionHead", "ModelConfig", "ModelForObjectDetection", "ModelImageGuidedObjectDetectionOutput", "ModelModel", "ModelObjectDetectionOutput", "ModelPreTrainedModel", "None", "Sigmoid", "True", "_", "__init__", "all...
hubert/modeling_hubert.py:HubertPositionalConvEmbedding
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[ "ACT2FN", "BatchNorm1d", "Conv1d", "GatheredParameters", "ModelPositionalConvEmbedding", "ModelSamePadLayer", "Module", "None", "__init__", "activation", "batch_norm", "class", "config", "conv", "conv_pos_batch_norm", "deepspeed", "def", "dim", "else", "feat_extract_activation"...
hubert/modeling_hubert.py:HubertSamePadLayer
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[ "ModelSamePadLayer", "Module", "__init__", "class", "def", "else", "forward", "hidden_states", "if", "nn", "num_conv_pos_embeddings", "num_pad_remove", "return", "self", "super" ]
hubert/modeling_hubert.py:HubertNoLayerNormConvLayer
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[ "ACT2FN", "Conv1d", "GradientCheckpointingLayer", "ModelNoLayerNormConvLayer", "__init__", "activation", "class", "config", "conv", "conv_dim", "conv_kernel", "conv_stride", "def", "else", "feat_extract_activation", "forward", "hidden_states", "if", "in_conv_dim", "kernel_size"...
hubert/modeling_hubert.py:HubertLayerNormConvLayer
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[ "ACT2FN", "Conv1d", "GradientCheckpointingLayer", "LayerNorm", "ModelLayerNormConvLayer", "True", "__init__", "activation", "class", "config", "conv", "conv_dim", "conv_kernel", "conv_stride", "def", "elementwise_affine", "else", "feat_extract_activation", "forward", "hidden_st...
hubert/modeling_hubert.py:HubertGroupNormConvLayer
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[ "ACT2FN", "Conv1d", "GradientCheckpointingLayer", "GroupNorm", "ModelGroupNormConvLayer", "True", "__init__", "activation", "affine", "class", "config", "conv", "conv_dim", "conv_kernel", "conv_stride", "def", "else", "feat_extract_activation", "forward", "hidden_states", "if...
hubert/modeling_hubert.py:HubertFeatureEncoder
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[ "False", "ModelFeatureEncoder", "ModelGroupNormConvLayer", "ModelLayerNormConvLayer", "ModelNoLayerNormConvLayer", "Module", "ModuleList", "None", "True", "ValueError", "__init__", "_freeze_parameters", "_requires_grad", "and", "be", "but", "class", "config", "conv_layer", "con...
hubert/modeling_hubert.py:HubertFeatureProjection
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[ "Dropout", "LayerNorm", "Linear", "ModelFeatureProjection", "Module", "__init__", "class", "config", "conv_dim", "def", "dropout", "eps", "feat_proj_dropout", "feat_proj_layer_norm", "forward", "hidden_size", "hidden_states", "if", "layer_norm", "layer_norm_eps", "nn", "pro...
hubert/modeling_hubert.py:eager_attention_forward
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[ "Model_attention_forward", "None", "attention_mask", "attn_output", "attn_weights", "contiguous", "def", "dim", "dropout", "functional", "if", "is", "key", "kwargs", "matmul", "module", "nn", "not", "p", "query", "return", "scaling", "shape", "size", "softmax", "tor...
hubert/modeling_hubert.py:HubertAttention
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[ "ALL_ATTENTION_FUNCTIONS", "False", "Linear", "ModelAttention", "Module", "None", "ValueError", "__init__", "_attn_implementation", "and", "attention_interface", "attention_mask", "attn_output", "attn_weights", "be", "bsz", "by", "class", "config", "contiguous", "current_stat...
hubert/modeling_hubert.py:HubertFeedForward
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[ "ACT2FN", "Dropout", "Linear", "ModelFeedForward", "Module", "__init__", "activation_dropout", "class", "config", "def", "else", "forward", "hidden_act", "hidden_dropout", "hidden_size", "hidden_states", "if", "intermediate_act_fn", "intermediate_dense", "intermediate_dropout",...
hubert/modeling_hubert.py:HubertEncoderLayer
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[ "Dropout", "False", "GradientCheckpointingLayer", "LayerNorm", "ModelAttention", "ModelEncoderLayer", "ModelFeedForward", "None", "_", "__init__", "attention", "attention_dropout", "attention_mask", "attn_residual", "attn_weights", "class", "config", "def", "dropout", "embed_di...
hubert/modeling_hubert.py:HubertEncoder
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[ "BaseModelOutput", "Dropout", "False", "LayerNorm", "ModelEncoder", "ModelEncoderLayer", "ModelPositionalConvEmbedding", "Module", "ModuleList", "None", "True", "_", "__init__", "all_hidden_states", "all_self_attentions", "and", "attention_mask", "attentions", "class", "config"...
hubert/modeling_hubert.py:HubertAttnAdapterLayer
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hubert/modeling_hubert.py:HubertEncoderLayerStableLayerNorm
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[ "Dropout", "False", "GradientCheckpointingLayer", "LayerNorm", "ModelAttention", "ModelAttnAdapterLayer", "ModelEncoderLayerStableLayerNorm", "ModelFeedForward", "None", "_", "__init__", "adapter_attn_dim", "adapter_layer", "attention", "attention_dropout", "attention_mask", "attn_re...
hubert/modeling_hubert.py:HubertEncoderStableLayerNorm
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[ "BaseModelOutput", "Dropout", "False", "LayerNorm", "ModelEncoderLayerStableLayerNorm", "ModelEncoderStableLayerNorm", "ModelPositionalConvEmbedding", "Module", "ModuleList", "None", "True", "_", "__init__", "all_hidden_states", "all_self_attentions", "and", "attention_mask", "atte...
hubert/modeling_hubert.py:HubertPreTrainedModel
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[ "BatchNorm1d", "Conv1d", "GatheredParameters", "GroupNorm", "LayerNorm", "Linear", "Model", "ModelConfig", "ModelForSequenceClassification", "ModelModel", "ModelPreTrainedModel", "None", "PreTrainedModel", "True", "_conv_out_length", "_get_feat_extract_output_lengths", "_get_feature_...
hubert/modeling_hubert.py:_compute_mask_indices
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hubert/modeling_hubert.py:HubertModel
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hubert/modeling_hubert.py:HubertForCTC
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hubert/modeling_hubert.py:HubertForSequenceClassification
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convbert/modeling_convbert.py:ConvBertEmbeddings
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convbert/modeling_convbert.py:ConvBertPreTrainedModel
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convbert/modeling_convbert.py:SeparableConv1D
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convbert/modeling_convbert.py:ConvBertSelfAttention
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convbert/modeling_convbert.py:ConvBertSelfOutput
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convbert/modeling_convbert.py:ConvBertAttention
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convbert/modeling_convbert.py:GroupedLinearLayer
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convbert/modeling_convbert.py:ConvBertIntermediate
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convbert/modeling_convbert.py:ConvBertOutput
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convbert/modeling_convbert.py:ConvBertLayer
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convbert/modeling_convbert.py:ConvBertEncoder
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convbert/modeling_convbert.py:ConvBertPredictionHeadTransform
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convbert/modeling_convbert.py:ConvBertSequenceSummary
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convbert/modeling_convbert.py:ConvBertModel
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convbert/modeling_convbert.py:ConvBertGeneratorPredictions
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convbert/modeling_convbert.py:ConvBertForMaskedLM
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convbert/modeling_convbert.py:ConvBertClassificationHead
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convbert/modeling_convbert.py:ConvBertForSequenceClassification
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convbert/modeling_convbert.py:ConvBertForMultipleChoice
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convbert/modeling_convbert.py:ConvBertForTokenClassification
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convbert/modeling_convbert.py:ConvBertForQuestionAnswering
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granitemoehybrid/modeling_granitemoehybrid.py:rotate_half
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granitemoehybrid/modeling_granitemoehybrid.py:apply_rotary_pos_emb
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granitemoehybrid/modeling_granitemoehybrid.py:repeat_kv
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granitemoehybrid/modeling_granitemoehybrid.py:eager_attention_forward
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridAttention
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granitemoehybrid/modeling_granitemoehybrid.py:HybridMambaAttentionDynamicCache
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granitemoehybrid/modeling_granitemoehybrid.py:pad_tensor_by_size
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granitemoehybrid/modeling_granitemoehybrid.py:reshape_into_chunks
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granitemoehybrid/modeling_granitemoehybrid.py:segment_sum
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granitemoehybrid/modeling_granitemoehybrid.py:apply_mask_to_padding_states
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridMambaLayer
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridRMSNormGated
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridMLP
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridRotaryEmbedding
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridParallelExperts
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridTopKGating
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridMoE
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteFlashAttentionKwargs
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridRMSNorm
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridDecoderLayer
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridPreTrainedModel
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridModel
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granitemoehybrid/modeling_granitemoehybrid.py:load_balancing_loss_func
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granitemoehybrid/modeling_granitemoehybrid.py:GraniteMoeHybridForCausalLM
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gpt2/modeling_gpt2.py:eager_attention_forward
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gpt2/modeling_gpt2.py:GPT2Attention
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gpt2/modeling_gpt2.py:GPT2MLP
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gpt2/modeling_gpt2.py:GPT2Block
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gpt2/modeling_gpt2.py:GPT2SequenceSummary
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gpt2/modeling_gpt2.py:GPT2PreTrainedModel
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gpt2/modeling_gpt2.py:GPT2DoubleHeadsModelOutput
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gpt2/modeling_gpt2.py:GPT2Model
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gpt2/modeling_gpt2.py:GPT2LMHeadModel
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gpt2/modeling_gpt2.py:GPT2DoubleHeadsModel
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gpt2/modeling_gpt2.py:GPT2ForSequenceClassification
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gpt2/modeling_gpt2.py:GPT2ForTokenClassification
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gpt2/modeling_gpt2.py:GPT2ForQuestionAnswering
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arcee/modeling_arcee.py:ArceeMLP
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arcee/modeling_arcee.py:ArceeRMSNorm
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arcee/modeling_arcee.py:ArceeRotaryEmbedding
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arcee/modeling_arcee.py:rotate_half
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arcee/modeling_arcee.py:apply_rotary_pos_emb
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arcee/modeling_arcee.py:repeat_kv
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arcee/modeling_arcee.py:eager_attention_forward
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arcee/modeling_arcee.py:ArceeAttention
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