Datasets:
itazap
/
transformers_code_embeddings_v3

Dataset card Data Studio Files
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 Community
1
identifier
stringlengths
24
102
embedding
listlengths
2.56k
2.56k
tokens
listlengths
4
448
florence2/modeling_florence2.py:Florence2Model
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[ "AutoModel", "Image", "ModelModel", "ModelMultiModalProjector", "ModelPreTrainedModel", "ModelSeq2SeqModelOutput", "ModelVisionBackbone", "None", "Obtains", "True", "ValueError", "You", "__init__", "_checkpoint_conversion_mapping", "all", "and", "apply", "attention_mask", "attent...
florence2/modeling_florence2.py:shift_tokens_right
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[ "Model_tokens_right", "Modeled_input_ids", "None", "clone", "decoder_start_token_id", "def", "if", "input_ids", "is", "masked_fill_", "new_zeros", "pad_token_id", "return", "shape" ]
florence2/modeling_florence2.py:Florence2ForConditionalGeneration
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[ "False", "GenerationMixin", "Linear", "ModelForConditionalGeneration", "ModelModel", "ModelPreTrainedModel", "ModelSeq2SeqLMOutput", "None", "True", "__init__", "_checkpoint_conversion_mapping", "_prepare_encoder_decoder_kwargs_for_generation", "_tied_weights_keys", "and", "attention_mas...
vit/modeling_vit.py:ViTEmbeddings
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[ "Dropout", "False", "ModelEmbeddings", "ModelPatchEmbeddings", "Module", "None", "Parameter", "__init__", "align_corners", "and", "batch_size", "bicubic", "bool_masked_pos", "cat", "class", "class_pos_embed", "cls_token", "cls_tokens", "config", "def", "dim", "dropout", "...
vit/modeling_vit.py:ViTPatchEmbeddings
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[ "Conv2d", "Expected", "False", "Input", "Iterable", "Make", "ModelPatchEmbeddings", "Module", "ValueError", "__init__", "abc", "batch_size", "but", "channel", "class", "collections", "config", "configuration", "def", "dimension", "doesn", "else", "embeddings", "f", "f...
vit/modeling_vit.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...
vit/modeling_vit.py:ViTSelfAttention
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[ "ALL_ATTENTION_FUNCTIONS", "False", "Linear", "ModelSelfAttention", "Module", "None", "The", "ValueError", "__init__", "_attn_implementation", "a", "all_head_size", "and", "attention", "attention_head_size", "attention_interface", "attention_probs", "attention_probs_dropout_prob", ...
vit/modeling_vit.py:ViTSelfOutput
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[ "Dropout", "Linear", "ModelSelfOutput", "Module", "__init__", "class", "config", "def", "dense", "dropout", "forward", "hidden_dropout_prob", "hidden_size", "hidden_states", "input_tensor", "nn", "return", "self", "super" ]
vit/modeling_vit.py:ViTAttention
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[ "ModelAttention", "ModelSelfAttention", "ModelSelfOutput", "Module", "_", "__init__", "attention", "class", "config", "def", "forward", "hidden_states", "nn", "output", "return", "self", "self_attn_output", "super" ]
vit/modeling_vit.py:ViTIntermediate
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[ "ACT2FN", "Linear", "ModelIntermediate", "Module", "__init__", "class", "config", "def", "dense", "else", "forward", "hidden_act", "hidden_size", "hidden_states", "if", "intermediate_act_fn", "intermediate_size", "isinstance", "nn", "return", "self", "str", "super" ]
vit/modeling_vit.py:ViTOutput
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[ "Dropout", "Linear", "ModelOutput", "Module", "__init__", "class", "config", "def", "dense", "dropout", "forward", "hidden_dropout_prob", "hidden_size", "hidden_states", "input_tensor", "intermediate_size", "nn", "return", "self", "super" ]
vit/modeling_vit.py:ViTLayer
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[ "GradientCheckpointingLayer", "LayerNorm", "ModelAttention", "ModelIntermediate", "ModelLayer", "ModelOutput", "__init__", "attention", "attention_output", "chunk_size_feed_forward", "class", "config", "def", "eps", "forward", "hidden_size", "hidden_states", "hidden_states_norm", ...
vit/modeling_vit.py:ViTEncoder
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[ "BaseModelOutput", "False", "ModelEncoder", "ModelLayer", "Module", "ModuleList", "_", "__init__", "class", "config", "def", "enumerate", "for", "forward", "gradient_checkpointing", "hidden_states", "i", "in", "last_hidden_state", "layer", "layer_module", "nn", "num_hidde...
vit/modeling_vit.py:ViTPreTrainedModel
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[ "Conv2d", "LayerNorm", "Linear", "Model", "ModelConfig", "ModelEmbeddings", "ModelLayer", "ModelPreTrainedModel", "ModelSelfAttention", "None", "PreTrainedModel", "True", "_can_record_outputs", "_init_weights", "_no_split_modules", "_supports_attention_backend", "_supports_flash_attn...
vit/modeling_vit.py:ViTModel
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[ "BaseModelOutputWithPooling", "False", "LayerNorm", "ModelEmbeddings", "ModelEncoder", "ModelModel", "ModelPooler", "ModelPreTrainedModel", "None", "True", "__init__", "add_pooling_layer", "auto_docstring", "bool_masked_pos", "check_model_inputs", "class", "config", "def", "dtype...
vit/modeling_vit.py:ViTPooler
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[ "ACT2FN", "Linear", "ModelPooler", "Module", "__init__", "activation", "class", "config", "def", "dense", "first_token_tensor", "forward", "hidden_size", "hidden_states", "nn", "pooled_output", "pooler_act", "pooler_output_size", "return", "self", "super" ]
vit/modeling_vit.py:ViTForMaskedImageModeling
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[ "Conv2d", "False", "Got", "MaskedImageModelingOutput", "Model", "ModelForMaskedImageModeling", "ModelModel", "ModelPreTrainedModel", "None", "PixelShuffle", "Sequential", "True", "ValueError", "When", "__init__", "add_pooling_layer", "and", "as", "attentions", "auto_docstring",...
vit/modeling_vit.py:ViTForImageClassification
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[ "False", "Identity", "ImageClassifierOutput", "Linear", "Model", "ModelForImageClassification", "ModelModel", "ModelPreTrainedModel", "None", "__init__", "add_pooling_layer", "attentions", "auto_docstring", "can_return_tuple", "class", "classifier", "config", "def", "else", "fo...
longformer/modeling_longformer.py:LongformerBaseModelOutput
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[ "FloatTensor", "ModelBaseModelOutput", "ModelOutput", "None", "attentions", "class", "global_attentions", "hidden_states", "last_hidden_state", "r", "torch" ]
longformer/modeling_longformer.py:LongformerBaseModelOutputWithPooling
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[ "FloatTensor", "ModelBaseModelOutputWithPooling", "ModelOutput", "None", "attentions", "class", "global_attentions", "hidden_states", "last_hidden_state", "pooler_output", "r", "torch" ]
longformer/modeling_longformer.py:LongformerMaskedLMOutput
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[ "ModelMaskedLMOutput", "ModelOutput", "None", "attentions", "class", "global_attentions", "hidden_states", "logits", "loss", "r" ]
longformer/modeling_longformer.py:LongformerQuestionAnsweringModelOutput
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[ "ModelOutput", "ModelQuestionAnsweringModelOutput", "None", "attentions", "class", "end_logits", "global_attentions", "hidden_states", "loss", "r", "start_logits" ]
longformer/modeling_longformer.py:LongformerSequenceClassifierOutput
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[ "ModelOutput", "ModelSequenceClassifierOutput", "None", "attentions", "class", "global_attentions", "hidden_states", "logits", "loss", "r" ]
longformer/modeling_longformer.py:LongformerMultipleChoiceModelOutput
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[ "ModelMultipleChoiceModelOutput", "ModelOutput", "None", "attentions", "class", "global_attentions", "hidden_states", "logits", "loss", "r" ]
longformer/modeling_longformer.py:LongformerTokenClassifierOutput
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[ "ModelOutput", "ModelTokenClassifierOutput", "None", "attentions", "class", "global_attentions", "hidden_states", "logits", "loss", "r" ]
longformer/modeling_longformer.py:_get_question_end_index
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[ "There", "You", "_get_question_end_index", "also", "answering", "assert", "avoid", "batch_size", "be", "consider", "def", "dimensions", "error", "every", "exactly", "f", "for", "forward", "function", "global_attention_mask", "have", "in", "input_ids", "manually", "mig...
longformer/modeling_longformer.py:_compute_global_attention_mask
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[ "True", "_compute_global_attention_mask", "_get_question_end_index", "arange", "attention_mask", "before_sep_token", "bool", "def", "device", "dim", "else", "expand_as", "if", "input_ids", "is", "question_end_index", "return", "sep_token_id", "shape", "to", "torch", "unsque...
longformer/modeling_longformer.py:create_position_ids_from_input_ids
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[ "Model_position_ids_from_input_ids", "cumsum", "def", "dim", "incremental_indices", "input_ids", "int", "long", "mask", "ne", "padding_idx", "return", "torch", "type_as" ]
longformer/modeling_longformer.py:LongformerEmbeddings
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[ "Dropout", "Embedding", "LayerNorm", "ModelEmbeddings", "Module", "None", "__init__", "arange", "class", "config", "create_position_ids_from_input_ids", "create_position_ids_from_inputs_embeds", "def", "device", "dropout", "dtype", "else", "embeddings", "eps", "expand", "forw...
longformer/modeling_longformer.py:LongformerSelfAttention
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[ "False", "Given", "Linear", "ModelSelfAttention", "Module", "None", "Sequence", "Size", "The", "True", "Unexpected", "ValueError", "__init__", "_chunk", "_compute_attn_output_with_global_indices", "_compute_global_attn_output_from_hidden", "_concat_with_global_key_attn_probs", "_ge...
longformer/modeling_longformer.py:LongformerSelfOutput
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[ "Dropout", "LayerNorm", "Linear", "ModelSelfOutput", "Module", "__init__", "class", "config", "def", "dense", "dropout", "eps", "forward", "hidden_dropout_prob", "hidden_size", "hidden_states", "input_tensor", "layer_norm_eps", "nn", "return", "self", "super" ]
longformer/modeling_longformer.py:LongformerAttention
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[ "False", "ModelAttention", "ModelSelfAttention", "ModelSelfOutput", "Module", "None", "__init__", "attention_mask", "attn_output", "class", "config", "def", "forward", "hidden_states", "is_global_attn", "is_index_global_attn", "is_index_masked", "layer_id", "nn", "output", "o...
longformer/modeling_longformer.py:LongformerIntermediate
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longformer/modeling_longformer.py:LongformerOutput
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longformer/modeling_longformer.py:LongformerLayer
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longformer/modeling_longformer.py:LongformerEncoder
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longformer/modeling_longformer.py:LongformerPooler
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longformer/modeling_longformer.py:LongformerLMHead
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longformer/modeling_longformer.py:LongformerPreTrainedModel
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longformer/modeling_longformer.py:LongformerModel
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longformer/modeling_longformer.py:LongformerForMaskedLM
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longformer/modeling_longformer.py:LongformerForSequenceClassification
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longformer/modeling_longformer.py:LongformerClassificationHead
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longformer/modeling_longformer.py:LongformerForQuestionAnswering
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longformer/modeling_longformer.py:LongformerForTokenClassification
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longformer/modeling_longformer.py:LongformerForMultipleChoice
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olmo3/modeling_olmo3.py:Olmo3RMSNorm
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olmo3/modeling_olmo3.py:repeat_kv
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olmo3/modeling_olmo3.py:eager_attention_forward
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olmo3/modeling_olmo3.py:apply_rotary_pos_emb
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olmo3/modeling_olmo3.py:rotate_half
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olmo3/modeling_olmo3.py:Olmo3Attention
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olmo3/modeling_olmo3.py:Olmo3MLP
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olmo3/modeling_olmo3.py:Olmo3DecoderLayer
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olmo3/modeling_olmo3.py:Olmo3RotaryEmbedding
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olmo3/modeling_olmo3.py:Olmo3PreTrainedModel
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olmo3/modeling_olmo3.py:Olmo3Model
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olmo3/modeling_olmo3.py:Olmo3ForCausalLM
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reformer/modeling_reformer.py:ReformerDynamicCache
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reformer/modeling_reformer.py:_stable_argsort
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reformer/modeling_reformer.py:_get_least_common_mult_chunk_len
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reformer/modeling_reformer.py:_get_min_chunk_len
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reformer/modeling_reformer.py:AxialPositionEmbeddings
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reformer/modeling_reformer.py:PositionEmbeddings
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reformer/modeling_reformer.py:ReformerEmbeddings
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reformer/modeling_reformer.py:EfficientAttentionMixin
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reformer/modeling_reformer.py:LSHSelfAttention
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reformer/modeling_reformer.py:ReverseSort
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reformer/modeling_reformer.py:LocalSelfAttention
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reformer/modeling_reformer.py:ReformerSelfOutput
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reformer/modeling_reformer.py:ReformerAttention
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reformer/modeling_reformer.py:ReformerFeedForwardDense
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reformer/modeling_reformer.py:ReformerFeedForwardOutput
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reformer/modeling_reformer.py:ChunkReformerFeedForward
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reformer/modeling_reformer.py:ReformerLayer
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reformer/modeling_reformer.py:_ReversibleFunction
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reformer/modeling_reformer.py:ReformerEncoder
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reformer/modeling_reformer.py:ReformerOnlyLMHead
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reformer/modeling_reformer.py:ReformerPreTrainedModel
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reformer/modeling_reformer.py:ReformerModelOutput
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reformer/modeling_reformer.py:ReformerModelWithLMHeadOutput
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reformer/modeling_reformer.py:ReformerModel
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reformer/modeling_reformer.py:ReformerModelWithLMHead
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reformer/modeling_reformer.py:ReformerForMaskedLM
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reformer/modeling_reformer.py:ReformerForSequenceClassification
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reformer/modeling_reformer.py:ReformerClassificationHead
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reformer/modeling_reformer.py:ReformerForQuestionAnswering
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visual_bert/modeling_visual_bert.py:VisualBertEmbeddings
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visual_bert/modeling_visual_bert.py:VisualBertSelfAttention
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visual_bert/modeling_visual_bert.py:VisualBertSelfOutput
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visual_bert/modeling_visual_bert.py:VisualBertAttention
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visual_bert/modeling_visual_bert.py:VisualBertIntermediate
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visual_bert/modeling_visual_bert.py:VisualBertOutput
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visual_bert/modeling_visual_bert.py:VisualBertLayer
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visual_bert/modeling_visual_bert.py:VisualBertEncoder
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visual_bert/modeling_visual_bert.py:VisualBertPooler
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visual_bert/modeling_visual_bert.py:VisualBertPredictionHeadTransform
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visual_bert/modeling_visual_bert.py:VisualBertLMPredictionHead
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visual_bert/modeling_visual_bert.py:VisualBertPreTrainingHeads
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visual_bert/modeling_visual_bert.py:VisualBertPreTrainedModel
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[ "Embedding", "LayerNorm", "Linear", "Model", "ModelConfig", "ModelEmbeddings", "ModelLMPredictionHead", "ModelPreTrainedModel", "None", "PreTrainedModel", "True", "_init_weights", "and", "arange", "base_model_prefix", "bias", "class", "config", "copy_", "def", "elif", "expa...