Datasets:
itazap
/
transformers_code_embeddings_v3

Dataset card Data Studio Files
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1
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24
117
embedding
listlengths
2.56k
2.56k
tokens
listlengths
4
448
depth_pro/modeling_depth_pro.py:DepthProFovModel
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[ "Conv2d", "ModelFovEncoder", "ModelFovHead", "ModelFovModel", "Module", "ReLU", "True", "__init__", "activation", "class", "config", "conv", "def", "flatten", "forward", "fov_encoder", "fov_features", "fov_output", "fusion_hidden_size", "global_features", "head", "inplace",...
depth_pro/modeling_depth_pro.py:DepthProDepthEstimationHead
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[ "Conv2d", "ConvTranspose2d", "ModelModelEstimationHead", "Module", "ModuleList", "ReLU", "True", "__init__", "class", "config", "def", "dim", "features", "for", "forward", "fusion_hidden_size", "hidden_states", "in", "in_channels", "kernel_size", "layer", "layers", "nn", ...
depth_pro/modeling_depth_pro.py:DepthProForDepthEstimation
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[ "Model", "ModelFeatureFusionStage", "ModelForModelEstimation", "ModelFovModel", "ModelModel", "ModelModelEstimationHead", "ModelModelEstimatorOutput", "ModelPreTrainedModel", "Model_outputs", "None", "True", "__init__", "attentions", "auto_docstring", "class", "config", "def", "det...
mllama/modeling_mllama.py:_prepare_cross_attention_mask
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[ "None", "_", "_prepare_cross_attention_mask", "any", "batch_size", "bool", "cross_attention_mask", "def", "dim", "dtype", "finfo", "full_text_row_masked_out_mask", "inverted_cross_attn_mask", "masked_fill", "min", "negative_inf_value", "num_vision_tokens", "repeat_interleave", "r...
mllama/modeling_mllama.py:_prepare_aspect_ratio_attention_mask
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[ "_prepare_aspect_ratio_attention_mask", "aspect_ratio_mask", "attention_mask", "batch_size", "def", "dtype", "finfo", "max_num_tiles", "min", "num_patches", "pad_patches", "repeat", "reshape", "return", "shape", "target_length", "torch", "transpose", "unsqueeze", "view" ]
mllama/modeling_mllama.py:MllamaPrecomputedAspectRatioEmbedding
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[ "Embedding", "ModelPrecomputedAspectRatioEmbedding", "Module", "Parameter", "True", "__init__", "aspect_ratio_ids", "class", "config", "def", "embedding", "embeddings", "forward", "gate", "hidden_size", "hidden_state", "if", "is_gated", "max_aspect_ratio_id", "max_num_tiles", ...
mllama/modeling_mllama.py:MllamaPrecomputedPositionEmbedding
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[ "Embedding", "ModelPrecomputedPositionEmbedding", "Module", "Parameter", "__init__", "aspect_ratio_ids", "batch_size", "class", "config", "def", "embedding", "forward", "gate", "gated_position_embedding", "gated_tile_position_embedding", "hidden_size", "hidden_state", "image_size",...
mllama/modeling_mllama.py:MllamaVisionMLP
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[ "ACT2FN", "Linear", "ModelVisionMLP", "Module", "__init__", "activation_fn", "class", "config", "def", "fc1", "fc2", "forward", "hidden_act", "hidden_size", "hidden_states", "intermediate_size", "nn", "return", "self", "super" ]
mllama/modeling_mllama.py:repeat_kv
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[ "Model_kv", "None", "batch", "def", "expand", "head_dim", "hidden_states", "if", "n_rep", "num_key_value_heads", "reshape", "return", "shape", "slen" ]
mllama/modeling_mllama.py:eager_attention_forward
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[ "Model_attention_forward", "None", "attention_mask", "attn_output", "attn_weights", "contiguous", "def", "dim", "dropout", "dtype", "float32", "functional", "if", "is", "key", "key_states", "kwargs", "matmul", "module", "nn", "not", "num_key_value_groups", "p", "query",...
mllama/modeling_mllama.py:MllamaVisionAttention
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[ "ALL_ATTENTION_FUNCTIONS", "Linear", "ModelVisionAttention", "Module", "None", "_", "__init__", "_attn_implementation", "attention_heads", "attention_interface", "attention_mask", "attn_output", "attn_weights", "batch_size", "class", "config", "contiguous", "def", "dropout", "e...
mllama/modeling_mllama.py:MllamaVisionEncoderLayer
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[ "False", "LayerNorm", "ModelVisionAttention", "ModelVisionEncoderLayer", "ModelVisionMLP", "Module", "None", "Parameter", "__init__", "attention_heads", "attention_mask", "attn_weights", "class", "config", "def", "eps", "forward", "gate_attn", "gate_ffn", "hidden_size", "hidd...
mllama/modeling_mllama.py:MllamaVisionEncoder
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[ "BaseModelOutput", "False", "ModelVisionEncoder", "ModelVisionEncoderLayer", "Module", "ModuleList", "None", "_", "__init__", "attention_mask", "class", "config", "def", "encoder_layer", "encoder_states", "for", "forward", "gradient_checkpointing", "hidden_state", "hidden_state...
mllama/modeling_mllama.py:MllamaTextRMSNorm
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[ "ModelTextRMSNorm", "Module", "Parameter", "True", "__init__", "class", "def", "dtype", "eps", "extra_repr", "f", "float32", "forward", "hidden_size", "hidden_states", "input_dtype", "keepdim", "mean", "nn", "ones", "pow", "return", "rsqrt", "self", "shape", "super"...
mllama/modeling_mllama.py:MllamaTextCrossAttention
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[ "ALL_ATTENTION_FUNCTIONS", "Cross", "Linear", "ModelTextCrossAttention", "ModelTextRMSNorm", "Module", "None", "ValueError", "_", "__init__", "_attn_implementation", "attention", "attention_interface", "attention_mask", "attn_output", "attn_weights", "bsz", "cache_position", "cac...
mllama/modeling_mllama.py:rotate_half
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[ "Model_half", "cat", "def", "dim", "return", "shape", "torch", "x", "x1", "x2" ]
mllama/modeling_mllama.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" ]
mllama/modeling_mllama.py:MllamaTextSelfAttention
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[ "ALL_ATTENTION_FUNCTIONS", "Linear", "ModelTextSelfAttention", "Module", "None", "True", "_", "__init__", "_attn_implementation", "apply_rotary_pos_emb", "attention_interface", "attention_mask", "attn_output", "attn_weights", "bsz", "cache_kwargs", "cache_position", "class", "con...
mllama/modeling_mllama.py:MllamaTextMLP
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[ "ACT2FN", "Linear", "ModelTextMLP", "Module", "__init__", "act_fn", "class", "config", "def", "down_proj", "forward", "gate_proj", "hidden_act", "hidden_size", "intermediate_size", "nn", "return", "self", "super", "up_proj", "x" ]
mllama/modeling_mllama.py:MllamaSelfAttentionDecoderLayer
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[ "False", "GradientCheckpointingLayer", "ModelSelfAttentionDecoderLayer", "ModelTextMLP", "ModelTextRMSNorm", "ModelTextSelfAttention", "None", "Tensor", "__init__", "attention_mask", "cache_position", "class", "config", "cross_attention_mask", "cross_attention_states", "def", "eps", ...
mllama/modeling_mllama.py:MllamaCrossAttentionDecoderLayer
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[ "False", "GradientCheckpointingLayer", "ModelCrossAttentionDecoderLayer", "ModelTextCrossAttention", "ModelTextMLP", "ModelTextRMSNorm", "None", "Parameter", "Tensor", "__init__", "attention_mask", "attn_weights", "cache_position", "class", "config", "cross_attention_mask", "cross_at...
mllama/modeling_mllama.py:MllamaRotaryEmbedding
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[ "False", "ModelRotaryEmbedding", "Module", "None", "ROPE_INIT_FUNCTIONS", "Tensor", "__init__", "and", "arange", "attention_factor", "attention_scaling", "base", "cat", "class", "clone", "compute_default_rope_parameters", "config", "cos", "cpu", "def", "default", "device", ...
mllama/modeling_mllama.py:MllamaPreTrainedModel
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[ "Conv2d", "Embedding", "False", "LayerNorm", "Linear", "ModelConfig", "ModelCrossAttentionDecoderLayer", "ModelPreTrainedModel", "ModelPrecomputedAspectRatioEmbedding", "ModelPrecomputedPositionEmbedding", "ModelRotaryEmbedding", "ModelSelfAttentionDecoderLayer", "ModelTextCrossAttention", ...
mllama/modeling_mllama.py:MllamaVisionModel
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[ "BaseModelOutput", "Conv2d", "F", "False", "LayerNorm", "ModelPreTrainedModel", "ModelPrecomputedAspectRatioEmbedding", "ModelPrecomputedPositionEmbedding", "ModelVisionConfig", "ModelVisionEncoder", "ModelVisionModel", "None", "Parameter", "True", "_", "__init__", "_prepare_aspect_r...
mllama/modeling_mllama.py:MllamaTextModel
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[ "BaseModelOutputWithPast", "DynamicCache", "Embedding", "False", "ModelPreTrainedModel", "ModelRotaryEmbedding", "ModelTextConfig", "ModelTextModel", "ModelTextRMSNorm", "ModuleList", "None", "Tensor", "ValueError", "You", "__init__", "and", "arange", "attention_mask", "auto_docs...
mllama/modeling_mllama.py:MllamaForCausalLM
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[ "CausalLMOutputWithPast", "GenerationMixin", "Linear", "ModelForCausalLM", "ModelPreTrainedModel", "ModelTextConfig", "ModelTextModel", "None", "Tensor", "True", "__init__", "_can_compile_fullgraph", "_from_config", "attention_mask", "attentions", "auto_docstring", "base_model_prefix...
mllama/modeling_mllama.py:MllamaModel
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[ "BaseModelOutputWithPast", "Linear", "ModelModel", "ModelPreTrainedModel", "ModelTextModel", "ModelVisionModel", "None", "ValueError", "You", "__init__", "_checkpoint_conversion_mapping", "_from_config", "_prepare_cross_attention_mask", "and", "aspect_ratio_ids", "aspect_ratio_mask", ...
mllama/modeling_mllama.py:MllamaForConditionalGeneration
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[ "CausalLMOutputWithPast", "False", "GenerationMixin", "Linear", "ModelForConditionalGeneration", "ModelModel", "ModelPreTrainedModel", "None", "__init__", "_checkpoint_conversion_mapping", "_update_model_kwargs_for_generation", "and", "aspect_ratio_ids", "aspect_ratio_mask", "attention_m...
cohere2_vision/modeling_cohere2_vision.py:Cohere2VisionMultiModalProjector
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[ "Linear", "ModelMultiModalProjector", "Module", "SiLU", "__init__", "act", "alignment_intermediate_size", "batch_size", "channels", "chunk", "class", "config", "def", "dim", "downsample_factor", "feature_dim", "forward", "gate", "height", "hidden_size", "hidden_states", "im...
cohere2_vision/modeling_cohere2_vision.py:Cohere2VisionModelOutputWithPast
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[ "BaseModelOutputWithPast", "ModelModelOutputWithPast", "None", "class", "image_hidden_states", "r" ]
cohere2_vision/modeling_cohere2_vision.py:Cohere2VisionCausalLMOutputWithPast
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[ "ModelCausalLMOutputWithPast", "ModelOutput", "None", "attentions", "class", "hidden_states", "image_hidden_states", "logits", "loss", "past_key_values", "r" ]
cohere2_vision/modeling_cohere2_vision.py:Cohere2VisionPreTrainedModel
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cohere2_vision/modeling_cohere2_vision.py:Cohere2VisionModel
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cohere2_vision/modeling_cohere2_vision.py:Cohere2VisionForConditionalGeneration
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bigbird_pegasus/modeling_bigbird_pegasus.py:shift_tokens_right
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusLearnedPositionalEmbedding
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusScaledWordEmbedding
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusSelfAttention
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusBlockSparseAttention
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusEncoderAttention
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bigbird_pegasus/modeling_bigbird_pegasus.py:eager_attention_forward
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusDecoderAttention
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusEncoderLayer
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusDecoderLayer
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusClassificationHead
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusPreTrainedModel
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusEncoder
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusDecoder
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusModel
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusForConditionalGeneration
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusForSequenceClassification
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusForQuestionAnswering
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusDecoderWrapper
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bigbird_pegasus/modeling_bigbird_pegasus.py:BigBirdPegasusForCausalLM
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perception_lm/modeling_perception_lm.py:PerceptionLMAdaptiveAvgPooling
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perception_lm/modeling_perception_lm.py:PerceptionLMMultiModalProjector
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perception_lm/modeling_perception_lm.py:PerceptionLMPreTrainedModel
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perception_lm/modeling_perception_lm.py:PerceptionLMModelOutputWithPast
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perception_lm/modeling_perception_lm.py:PerceptionLMCausalLMOutputWithPast
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perception_lm/modeling_perception_lm.py:PerceptionLMModel
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perception_lm/modeling_perception_lm.py:PerceptionLMForConditionalGeneration
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pvt_v2/modeling_pvt_v2.py:drop_path
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pvt_v2/modeling_pvt_v2.py:PvtV2DropPath
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pvt_v2/modeling_pvt_v2.py:PvtV2OverlapPatchEmbeddings
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pvt_v2/modeling_pvt_v2.py:PvtV2DepthWiseConv
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pvt_v2/modeling_pvt_v2.py:PvtV2SelfAttention
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pvt_v2/modeling_pvt_v2.py:PvtV2ConvFeedForwardNetwork
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pvt_v2/modeling_pvt_v2.py:PvtV2BlockLayer
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pvt_v2/modeling_pvt_v2.py:PvtV2EncoderLayer
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pvt_v2/modeling_pvt_v2.py:PvtV2Encoder
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pvt_v2/modeling_pvt_v2.py:PvtV2PreTrainedModel
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x_clip/modeling_x_clip.py:contrastive_loss
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x_clip/modeling_x_clip.py:XCLIPVisionEmbeddings
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x_clip/modeling_x_clip.py:XCLIPTextEmbeddings
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x_clip/modeling_x_clip.py:XCLIPAttention
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x_clip/modeling_x_clip.py:XCLIPEncoderLayer
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x_clip/modeling_x_clip.py:drop_path
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x_clip/modeling_x_clip.py:XCLIPVisionEncoderLayer
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x_clip/modeling_x_clip.py:XCLIPPreTrainedModel
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x_clip/modeling_x_clip.py:XCLIPEncoder
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x_clip/modeling_x_clip.py:XCLIPTextTransformer
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x_clip/modeling_x_clip.py:XCLIPTextModel
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x_clip/modeling_x_clip.py:XCLIPVisionEncoder
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x_clip/modeling_x_clip.py:XCLIPVisionTransformer
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x_clip/modeling_x_clip.py:XCLIPVisionModel
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x_clip/modeling_x_clip.py:XCLIPMultiframeIntegrationTransformer
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x_clip/modeling_x_clip.py:XCLIPCrossAttention
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x_clip/modeling_x_clip.py:PromptGeneratorLayer
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x_clip/modeling_x_clip.py:XCLIPPromptGenerator
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x_clip/modeling_x_clip.py:XCLIPModel
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data2vec/modeling_data2vec_vision.py:Data2VecVisionModelOutputWithPooling
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[ "BaseModelOutputWithPooling", "ModelVisionModelOutputWithPooling", "class", "r" ]
data2vec/modeling_data2vec_vision.py:drop_path
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