Datasets:
itazap
/
transformers_code_embeddings_v3

Dataset card Data Studio Files
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1
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24
117
embedding
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2.56k
2.56k
tokens
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4
444
florence2/modeling_florence2.py:Florence2VisionWindowAttention
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[ "ALL_ATTENTION_FUNCTIONS", "F", "False", "Linear", "ModelVisionWindowAttention", "Module", "None", "_", "__init__", "_attn_implementation", "attention_interface", "attention_mask", "batch_size", "class", "config", "contiguous", "def", "dim", "eager_attention_forward", "embed_di...
florence2/modeling_florence2.py:Florence2VisionSpatialBlock
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[ "Conv2d", "Identity", "LayerNorm", "ModelDropPath", "ModelVisionMLP", "ModelVisionSpatialBlock", "ModelVisionWindowAttention", "Module", "__init__", "batch_size", "class", "config", "conv1", "conv2", "def", "drop_path1", "drop_path2", "drop_path_rate", "else", "embed_dim", "f...
florence2/modeling_florence2.py:Florence2VisionBlock
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[ "ModelVisionBlock", "ModelVisionChannelBlock", "ModelVisionSpatialBlock", "Module", "__init__", "channel_block", "channel_drop_path_rate", "class", "config", "def", "drop_path_rate", "forward", "hidden_states", "nn", "return", "self", "spatial_block", "spatial_drop_path_rate", "s...
florence2/modeling_florence2.py:Florence2VisionPreTrainedModel
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[ "ModelVisionBlock", "ModelVisionChannelAttention", "ModelVisionConfig", "ModelVisionPreTrainedModel", "ModelVisionWindowAttention", "PreTrainedModel", "True", "_can_compile_fullgraph", "_can_record_outputs", "_supports_flash_attn", "_supports_flex_attn", "_supports_sdpa", "attentions", "cl...
florence2/modeling_florence2.py:Florence2VisionBackbone
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[ "BaseModelOutputWithPooling", "Expected", "ModelVisionBackbone", "ModelVisionBlock", "ModelVisionConvEmbed", "ModelVisionPreTrainedModel", "ModuleList", "ValueError", "__init__", "append", "block", "block_idx", "blocks", "capture_outputs", "channel_drop_path_rate", "class", "config",...
florence2/modeling_florence2.py:Florence2MultiModalProjector
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[ "LayerNorm", "Linear", "ModelMultiModalProjector", "ModelVisionLearnedAbsolutePositionEmbedding2D", "ModelVisionPositionalEmbeddingCosine1D", "Module", "__init__", "cat", "class", "config", "def", "dim", "embed_dim", "flatten", "forward", "image_features", "image_position_embed", "...
florence2/modeling_florence2.py:Florence2Seq2SeqModelOutput
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[ "ModelSeq2SeqModelOutput", "None", "Seq2SeqModelOutput", "class", "image_hidden_states", "r" ]
florence2/modeling_florence2.py:Florence2Seq2SeqLMOutput
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[ "ModelSeq2SeqLMOutput", "None", "Seq2SeqLMOutput", "class", "image_hidden_states", "r" ]
florence2/modeling_florence2.py:Florence2PreTrainedModel
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[ "False", "ModelConfig", "ModelPreTrainedModel", "ModelVisionPositionalEmbeddingCosine1D", "PreTrainedModel", "True", "_can_compile_fullgraph", "_init_weights", "_skip_keys_device_placement", "_supports_attention_backend", "_supports_flash_attn", "_supports_flex_attn", "_supports_sdpa", "ba...
florence2/modeling_florence2.py:Florence2Model
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[ "AutoModel", "Image", "ModelModel", "ModelMultiModalProjector", "ModelPreTrainedModel", "ModelSeq2SeqModelOutput", "ModelVisionBackbone", "None", "Obtains", "ValueError", "You", "__init__", "all", "and", "apply", "attention_mask", "attentions", "auto_docstring", "can_return_tuple...
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", "__init__", "_prepare_encoder_decoder_kwargs_for_generation", "_tied_weights_keys", "and", "attention_mask", "auto_docstring", "can_return_tuple", ...
mvp/modeling_mvp.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" ]
mvp/modeling_mvp.py:MvpLearnedPositionalEmbedding
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[ "Embedding", "ModelLearnedPositionalEmbedding", "None", "__init__", "arange", "bsz", "class", "def", "device", "dtype", "else", "embedding_dim", "expand", "forward", "if", "input_ids", "is", "long", "nn", "num_embeddings", "offset", "past_key_values_length", "position_ids...
mvp/modeling_mvp.py:MvpAttention
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[ "Attention", "EncoderDecoderCache", "False", "Linear", "ModelAttention", "Module", "None", "True", "ValueError", "_", "__init__", "and", "attention_mask", "attn_output", "attn_probs", "attn_prompt", "attn_weights", "attn_weights_reshaped", "be", "bmm", "bsz", "but", "by",...
mvp/modeling_mvp.py:MvpEncoderLayer
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[ "ACT2FN", "False", "GradientCheckpointingLayer", "LayerNorm", "Linear", "ModelAttention", "ModelEncoderLayer", "__init__", "activation_dropout", "activation_fn", "activation_function", "all", "and", "attention_dropout", "attention_mask", "attn_prompt", "attn_weights", "clamp", "c...
mvp/modeling_mvp.py:MvpDecoderLayer
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[ "ACT2FN", "False", "GradientCheckpointingLayer", "LayerNorm", "Linear", "ModelAttention", "ModelDecoderLayer", "None", "True", "__init__", "activation_dropout", "activation_fn", "activation_function", "attention_dropout", "attention_mask", "attn_prompt", "class", "config", "cross...
mvp/modeling_mvp.py:MvpClassificationHead
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[ "Dropout", "Linear", "ModelClassificationHead", "Module", "__init__", "class", "def", "dense", "dropout", "forward", "hidden_states", "inner_dim", "input_dim", "nn", "num_classes", "out_proj", "p", "pooler_dropout", "return", "self", "super", "tanh", "torch" ]
mvp/modeling_mvp.py:MvpPrompt
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[ "Dropout", "Embedding", "GELU", "Linear", "ModelPrompt", "Module", "Sequential", "__init__", "class", "config", "d_model", "def", "dropout", "forward", "head_dim", "nn", "num_heads", "num_layers", "p", "permute", "prompt", "prompt_embedding", "prompt_ids", "prompt_lengt...
mvp/modeling_mvp.py:MvpPreTrainedModel
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[ "ModelConfig", "ModelForConditionalGeneration", "ModelPreTrainedModel", "PreTrainedModel", "True", "_init_weights", "attention_mask", "base_model_prefix", "class", "config", "def", "device", "dummy_inputs", "final_logits_bias", "if", "init", "input_ids", "isinstance", "model", ...
mvp/modeling_mvp.py:MvpEncoder
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[ "BaseModelOutput", "Embedding", "False", "LayerNorm", "ModelEncoder", "ModelEncoderLayer", "ModelLearnedPositionalEmbedding", "ModelPreTrainedModel", "ModelPrompt", "ModuleList", "None", "True", "_", "__init__", "all_attentions", "and", "arange", "attention_mask", "attentions", ...
mvp/modeling_mvp.py:MvpDecoder
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[ "BaseModelOutputWithPastAndCrossAttentions", "DynamicCache", "Embedding", "EncoderDecoderCache", "False", "LayerNorm", "ModelDecoder", "ModelDecoderLayer", "ModelLearnedPositionalEmbedding", "ModelPreTrainedModel", "ModelPrompt", "ModuleList", "None", "Setting", "True", "__init__", "...
mvp/modeling_mvp.py:MvpModel
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[ "BaseModelOutput", "Embedding", "False", "If", "ModelDecoder", "ModelEncoder", "ModelModel", "ModelPreTrainedModel", "None", "Please", "Seq2SeqModelOutput", "True", "ValueError", "__init__", "_keys_to_ignore_on_load_unexpected", "_tied_weights_keys", "and", "are", "assert", "at...
mvp/modeling_mvp.py:MvpForConditionalGeneration
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[ "CrossEntropyLoss", "False", "GenerationMixin", "Linear", "ModelForConditionalGeneration", "ModelModel", "ModelPreTrainedModel", "None", "Seq2SeqLMOutput", "True", "__init__", "_resize_final_logits_bias", "_tied_weights_keys", "and", "attention_mask", "auto_docstring", "cat", "clas...
mvp/modeling_mvp.py:MvpForSequenceClassification
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[ "All", "BCEWithLogitsLoss", "CrossEntropyLoss", "Each", "False", "MSELoss", "ModelClassificationHead", "ModelForSequenceClassification", "ModelModel", "ModelPreTrainedModel", "None", "NotImplementedError", "Passing", "Seq2SeqSequenceClassifierOutput", "__class__", "__init__", "__name...
mvp/modeling_mvp.py:MvpForQuestionAnswering
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[ "CrossEntropyLoss", "False", "Linear", "ModelForQuestionAnswering", "ModelModel", "ModelPreTrainedModel", "None", "Seq2SeqQuestionAnsweringModelOutput", "__init__", "and", "attention_mask", "auto_docstring", "clamp", "class", "config", "contiguous", "cross_attentions", "decoder_att...
mvp/modeling_mvp.py:MvpDecoderWrapper
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[ "ModelDecoder", "ModelDecoderWrapper", "ModelPreTrainedModel", "__init__", "args", "class", "config", "decoder", "def", "forward", "kwargs", "post_init", "return", "self", "super" ]
mvp/modeling_mvp.py:MvpForCausalLM
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[ "CausalLMOutputWithCrossAttentions", "CrossEntropyLoss", "False", "GenerationMixin", "Linear", "ModelDecoderWrapper", "ModelForCausalLM", "ModelPreTrainedModel", "None", "True", "__init__", "_tied_weights_keys", "attention_mask", "attentions", "auto_docstring", "class", "config", "...
ibert/modeling_ibert.py:IBertEmbeddings
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[ "Dropout", "False", "IntLayerNorm", "LayerNorm", "Model", "Module", "None", "QuantAct", "QuantEmbedding", "__init__", "act_bit", "arange", "class", "config", "create_position_ids_from_input_ids", "create_position_ids_from_inputs_embeds", "def", "device", "dropout", "dtype", "...
ibert/modeling_ibert.py:IBertSelfAttention
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[ "Dropout", "False", "IntSoftmax", "Model", "Module", "None", "QuantAct", "QuantLinear", "The", "True", "ValueError", "__init__", "a", "act_bit", "all_head_size", "and", "attention", "attention_head_size", "attention_mask", "attention_probs", "attention_probs_dropout_prob", ...
ibert/modeling_ibert.py:IBertSelfOutput
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[ "Dropout", "IntLayerNorm", "LayerNorm", "Model", "Module", "QuantAct", "QuantLinear", "True", "__init__", "act_bit", "bias_bit", "class", "config", "def", "dense", "dropout", "eps", "force_dequant", "forward", "hidden_dropout_prob", "hidden_size", "hidden_states", "hidden...
ibert/modeling_ibert.py:IBertAttention
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ibert/modeling_ibert.py:IBertIntermediate
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ibert/modeling_ibert.py:IBertOutput
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ibert/modeling_ibert.py:IBertLayer
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ibert/modeling_ibert.py:IBertEncoder
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ibert/modeling_ibert.py:IBertPooler
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ibert/modeling_ibert.py:IBertPreTrainedModel
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ibert/modeling_ibert.py:IBertModel
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ibert/modeling_ibert.py:IBertForMaskedLM
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ibert/modeling_ibert.py:IBertLMHead
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ibert/modeling_ibert.py:IBertForSequenceClassification
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ibert/modeling_ibert.py:IBertForMultipleChoice
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ibert/modeling_ibert.py:IBertForTokenClassification
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ibert/modeling_ibert.py:IBertClassificationHead
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ibert/modeling_ibert.py:IBertForQuestionAnswering
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ibert/modeling_ibert.py:create_position_ids_from_input_ids
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5Output
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[ "BaseModelOutput", "ModelOutput", "None", "class", "context_mu", "context_sigma", "loc", "r", "scale" ]
timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5OutputForPrediction
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5MLP
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5ResidualBlock
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5RMSNorm
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5RotaryEmbedding
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timesfm2_5/modeling_timesfm2_5.py:rotate_half
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[ "Model_half", "cat", "def", "dim", "return", "shape", "torch", "x", "x1", "x2" ]
timesfm2_5/modeling_timesfm2_5.py:apply_rotary_pos_emb
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[ "Model_rotary_pos_emb", "cos", "def", "k", "k_embed", "q", "q_embed", "return", "rotate_half", "sin", "unsqueeze", "unsqueeze_dim" ]
timesfm2_5/modeling_timesfm2_5.py:repeat_kv
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timesfm2_5/modeling_timesfm2_5.py:eager_attention_forward
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5Attention
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5DecoderLayer
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5PositionalEmbedding
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5PreTrainedModel
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5Model
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timesfm2_5/modeling_timesfm2_5.py:TimesFm2_5ModelForPrediction
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owlvit/modeling_owlvit.py:contrastive_loss
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owlvit/modeling_owlvit.py:image_text_contrastive_loss
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owlvit/modeling_owlvit.py:OwlViTOutput
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owlvit/modeling_owlvit.py:_upcast
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owlvit/modeling_owlvit.py:box_area
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owlvit/modeling_owlvit.py:box_iou
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owlvit/modeling_owlvit.py:generalized_box_iou
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owlvit/modeling_owlvit.py:OwlViTObjectDetectionOutput
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owlvit/modeling_owlvit.py:OwlViTImageGuidedObjectDetectionOutput
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owlvit/modeling_owlvit.py:OwlViTVisionEmbeddings
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owlvit/modeling_owlvit.py:OwlViTTextEmbeddings
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owlvit/modeling_owlvit.py:eager_attention_forward
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owlvit/modeling_owlvit.py:OwlViTAttention
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owlvit/modeling_owlvit.py:OwlViTMLP
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owlvit/modeling_owlvit.py:OwlViTEncoderLayer
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owlvit/modeling_owlvit.py:OwlViTPreTrainedModel
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owlvit/modeling_owlvit.py:OwlViTEncoder
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owlvit/modeling_owlvit.py:OwlViTTextTransformer
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owlvit/modeling_owlvit.py:OwlViTTextModel
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owlvit/modeling_owlvit.py:OwlViTVisionTransformer
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owlvit/modeling_owlvit.py:OwlViTVisionModel
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owlvit/modeling_owlvit.py:OwlViTModel
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owlvit/modeling_owlvit.py:OwlViTBoxPredictionHead
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owlvit/modeling_owlvit.py:OwlViTClassPredictionHead
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owlvit/modeling_owlvit.py:OwlViTForObjectDetection
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phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalVisionMLP
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phi4_multimodal/modeling_phi4_multimodal.py:simple_eager_attention_forward
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phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalVisionAttention
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phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalVisionEncoderLayer
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phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalVisionEncoder
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phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalVisionPreTrainedModel
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phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalVisionEmbeddings
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[ "Conv2d", "Embedding", "False", "ModelVisionEmbeddings", "Module", "None", "True", "_", "__init__", "align_corners", "and", "arange", "batch_size", "bicubic", "boundaries", "bucket_coords_h", "bucket_coords_w", "bucketize", "clamp", "class", "config", "def", "device", "...
phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalVisionMultiheadAttentionPoolingHead
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[ "LayerNorm", "ModelVisionMLP", "ModelVisionMultiheadAttentionPoolingHead", "Module", "MultiheadAttention", "Parameter", "True", "__init__", "attention", "attention_mask", "batch_first", "batch_size", "class", "config", "def", "eps", "forward", "hidden_size", "hidden_state", "ke...
phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalVisionModel
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[ "BaseModelOutputWithPooling", "False", "LayerNorm", "ModelVisionConfig", "ModelVisionEmbeddings", "ModelVisionEncoder", "ModelVisionModel", "ModelVisionMultiheadAttentionPoolingHead", "ModelVisionPreTrainedModel", "None", "__init__", "attention_mask", "batch_size", "bool", "capture_outpu...
phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalImageEmbedding
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[ "AvgPool2d", "Dropout", "False", "Linear", "ModelImageEmbedding", "ModelVisionModel", "Module", "None", "Parameter", "ReflectionPad2d", "True", "__init__", "_from_config", "accumulate", "append", "area_ratio", "as_tuple", "attention_mask", "base_feat_size", "batch_size", "bia...
phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalAudioMLP
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[ "ACT2FN", "Dropout", "LayerNorm", "Linear", "ModelAudioMLP", "Module", "__init__", "act_fn", "activation", "chunk", "class", "config", "def", "dim", "down_proj", "dropout", "dropout_rate", "forward", "gate", "gate_up_proj", "hidden_size", "hidden_states", "intermediate_si...
phi4_multimodal/modeling_phi4_multimodal.py:Phi4MultimodalAudioAttention
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[ "ALL_ATTENTION_FUNCTIONS", "Linear", "ModelAudioAttention", "Module", "True", "_", "__init__", "_attn_implementation", "attention_dropout", "attention_interface", "attention_mask", "attn_output", "class", "config", "contiguous", "def", "dropout", "dropout_rate", "else", "forwar...