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
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4
444
nanochat/modeling_nanochat.py:NanoChatAttention
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nanochat/modeling_nanochat.py:NanoChatMLP
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nanochat/modeling_nanochat.py:NanoChatDecoderLayer
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nanochat/modeling_nanochat.py:NanoChatPreTrainedModel
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nanochat/modeling_nanochat.py:NanoChatModel
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nanochat/modeling_nanochat.py:NanoChatForCausalLM
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sam3/modeling_sam3.py:Sam3VisionEncoderOutput
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sam3/modeling_sam3.py:Sam3GeometryEncoderOutput
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sam3/modeling_sam3.py:Sam3DETREncoderOutput
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sam3/modeling_sam3.py:Sam3DETRDecoderOutput
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[ "ModelDETRDecoderOutput", "ModelOutput", "None", "attentions", "class", "hidden_states", "intermediate_hidden_states", "presence_logits", "r", "reference_boxes" ]
sam3/modeling_sam3.py:Sam3MaskDecoderOutput
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[ "ModelMaskDecoderOutput", "ModelOutput", "None", "attentions", "class", "pred_masks", "r", "semantic_seg" ]
sam3/modeling_sam3.py:Sam3ImageSegmentationOutput
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sam3/modeling_sam3.py:inverse_sigmoid
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[ "Model_sigmoid", "clamp", "def", "eps", "log", "max", "min", "return", "torch", "x", "x1", "x2" ]
sam3/modeling_sam3.py:concat_padded_sequences
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sam3/modeling_sam3.py:box_cxcywh_to_xyxy
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sam3/modeling_sam3.py:Sam3MLP
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sam3/modeling_sam3.py:eager_attention_forward
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sam3/modeling_sam3.py:Sam3Attention
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sam3/modeling_sam3.py:Sam3ViTRotaryEmbedding
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sam3/modeling_sam3.py:rotate_pairwise
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[ "Model_pairwise", "def", "dim", "flatten", "return", "shape", "stack", "start_dim", "torch", "unbind", "view", "x", "x1", "x2" ]
sam3/modeling_sam3.py:apply_rotary_pos_emb_2d
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sam3/modeling_sam3.py:Sam3ViTRoPEAttention
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sam3/modeling_sam3.py:Sam3ViTPatchEmbeddings
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sam3/modeling_sam3.py:Sam3ViTEmbeddings
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sam3/modeling_sam3.py:window_partition
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sam3/modeling_sam3.py:window_unpartition
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sam3/modeling_sam3.py:Sam3ViTLayerScale
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sam3/modeling_sam3.py:Sam3ViTLayer
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sam3/modeling_sam3.py:Sam3PreTrainedModel
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sam3/modeling_sam3.py:Sam3ViTModel
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sam3/modeling_sam3.py:Sam3SinePositionEmbedding
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sam3/modeling_sam3.py:Sam3FPNLayer
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sam3/modeling_sam3.py:Sam3VisionNeck
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sam3/modeling_sam3.py:Sam3VisionModel
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sam3/modeling_sam3.py:Sam3GeometryEncoderLayer
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sam3/modeling_sam3.py:Sam3GeometryEncoder
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sam3/modeling_sam3.py:Sam3DetrEncoderLayer
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sam3/modeling_sam3.py:Sam3DetrEncoder
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sam3/modeling_sam3.py:Sam3DecoderMLP
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sam3/modeling_sam3.py:Sam3DetrDecoderLayer
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sam3/modeling_sam3.py:Sam3DetrDecoder
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sam3/modeling_sam3.py:Sam3DotProductScoring
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sam3/modeling_sam3.py:Sam3MaskEmbedder
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sam3/modeling_sam3.py:Sam3PixelDecoder
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sam3/modeling_sam3.py:Sam3MaskDecoder
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sam3/modeling_sam3.py:Sam3Model
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rwkv/modeling_rwkv.py:load_wkv_cuda_kernel
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rwkv/modeling_rwkv.py:RwkvLinearAttention
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rwkv/modeling_rwkv.py:rwkv_linear_attention_cpu
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rwkv/modeling_rwkv.py:rwkv_linear_attention
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rwkv/modeling_rwkv.py:RwkvSelfAttention
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rwkv/modeling_rwkv.py:RwkvFeedForward
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rwkv/modeling_rwkv.py:RwkvBlock
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rwkv/modeling_rwkv.py:RwkvPreTrainedModel
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rwkv/modeling_rwkv.py:RwkvOutput
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rwkv/modeling_rwkv.py:RwkvCausalLMOutput
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rwkv/modeling_rwkv.py:RwkvModel
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rwkv/modeling_rwkv.py:RwkvForCausalLM
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upernet/modeling_upernet.py:UperNetConvModule
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upernet/modeling_upernet.py:UperNetPyramidPoolingBlock
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upernet/modeling_upernet.py:UperNetPyramidPoolingModule
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upernet/modeling_upernet.py:UperNetHead
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upernet/modeling_upernet.py:UperNetFCNHead
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upernet/modeling_upernet.py:UperNetPreTrainedModel
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upernet/modeling_upernet.py:UperNetForSemanticSegmentation
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falcon_mamba/modeling_falcon_mamba.py:causal_conv1d_update
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falcon_mamba/modeling_falcon_mamba.py:causal_conv1d_fn
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falcon_mamba/modeling_falcon_mamba.py:rms_forward
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falcon_mamba/modeling_falcon_mamba.py:FalconMambaMixer
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falcon_mamba/modeling_falcon_mamba.py:FalconMambaRMSNorm
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falcon_mamba/modeling_falcon_mamba.py:FalconMambaBlock
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falcon_mamba/modeling_falcon_mamba.py:FalconMambaPreTrainedModel
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falcon_mamba/modeling_falcon_mamba.py:FalconMambaOutput
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falcon_mamba/modeling_falcon_mamba.py:FalconMambaCausalLMOutput
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falcon_mamba/modeling_falcon_mamba.py:FalconMambaModel
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falcon_mamba/modeling_falcon_mamba.py:FalconMambaForCausalLM
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rag/modeling_rag.py:RetrievAugLMMarginOutput
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rag/modeling_rag.py:RetrievAugLMOutput
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rag/modeling_rag.py:RagPreTrainedModel
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rag/modeling_rag.py:RagModel
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rag/modeling_rag.py:RagSequenceForGeneration
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rag/modeling_rag.py:RagTokenForGeneration
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hubert/modeling_hubert.py:HubertPositionalConvEmbedding
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hubert/modeling_hubert.py:HubertSamePadLayer
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hubert/modeling_hubert.py:HubertNoLayerNormConvLayer
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hubert/modeling_hubert.py:HubertLayerNormConvLayer
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hubert/modeling_hubert.py:HubertGroupNormConvLayer
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hubert/modeling_hubert.py:HubertFeatureEncoder
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hubert/modeling_hubert.py:HubertFeatureProjection
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hubert/modeling_hubert.py:eager_attention_forward
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hubert/modeling_hubert.py:HubertAttention
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hubert/modeling_hubert.py:HubertFeedForward
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hubert/modeling_hubert.py:HubertEncoderLayer
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hubert/modeling_hubert.py:HubertEncoder
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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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[ "Conv1d", "GatheredParameters", "Model", "ModelConfig", "ModelEncoderLayer", "ModelForSequenceClassification", "ModelModel", "ModelPreTrainedModel", "None", "ParametrizedConv1d", "PreTrainedModel", "True", "_conv_out_length", "_get_feat_extract_output_lengths", "_get_feature_vector_atten...
hubert/modeling_hubert.py:_compute_mask_indices
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[ "False", "None", "ValueError", "_", "_compute_mask_indices", "and", "append", "arange", "array", "attention_mask", "batch_size", "be", "bigger", "bool", "broadcast_to", "but", "choice", "compute_num_masked_span", "concatenate", "def", "detach", "dtype", "dummy_mask_idx", ...
hubert/modeling_hubert.py:HubertModel
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[ "BaseModelOutput", "ModelEncoder", "ModelEncoderStableLayerNorm", "ModelFeatureEncoder", "ModelFeatureProjection", "ModelModel", "ModelPreTrainedModel", "None", "Parameter", "Tensor", "True", "__init__", "_compute_mask_indices", "_get_feature_vector_attention_mask", "_mask_hidden_states"...