Datasets:
itazap
/
transformers_code_embeddings_v3

Dataset card Data Studio Files
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1
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24
102
embedding
listlengths
2.56k
2.56k
tokens
listlengths
4
448
sam2_video/modeling_sam2_video.py:Sam2VideoMaskDownSampler
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[ "ACT2FN", "Conv2d", "ModelMaskDownModelpler", "ModelMaskDownModelplerLayer", "Module", "ModuleList", "_", "__init__", "activation", "append", "class", "config", "def", "final_conv", "for", "forward", "in", "int", "kernel_size", "layer", "layers", "log2", "mask_downModelpl...
sam2_video/modeling_sam2_video.py:Sam2VideoMemoryEncoder
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[ "Conv2d", "ModelMaskDownModelpler", "ModelMemoryEncoder", "ModelMemoryFuser", "ModelPositionEmbeddingSine", "Module", "True", "__init__", "class", "config", "def", "device", "dtype", "feature_projection", "forward", "hidden_size", "kernel_size", "mask_downModelpler", "masks", "...
sam2_video/modeling_sam2_video.py:Sam2VideoPositionalEmbedding
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[ "ModelPositionalEmbedding", "Module", "None", "__init__", "cat", "class", "clone", "config", "coordinates", "cos", "def", "dim", "dtype", "float32", "forward", "hidden_size", "if", "input_coords", "input_shape", "is", "nn", "not", "np", "pi", "positional_embedding", ...
sam2_video/modeling_sam2_video.py:Sam2VideoVisionEncoderOutput
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[ "BaseModelOutputWithPooling", "ModelVisionEncoderOutput", "None", "class", "fpn_hidden_states", "fpn_position_encoding", "r" ]
sam2_video/modeling_sam2_video.py:Sam2VideoMaskEmbedding
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[ "ACT2FN", "Conv2d", "ModelLayerNorm", "ModelMaskEmbedding", "Module", "__init__", "activation", "channels_first", "class", "config", "conv1", "conv2", "conv3", "data_format", "def", "dense_embeddings", "eps", "forward", "hidden_act", "hidden_size", "hidden_states", "kernel_...
sam2_video/modeling_sam2_video.py:Sam2VideoPromptEncoder
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[ "Embedding", "ModelMaskEmbedding", "ModelPositionalEmbedding", "ModelPromptEncoder", "Module", "None", "Tensor", "__init__", "_embed_boxes", "_embed_points", "also", "batch_size", "be", "box_embeddings", "boxes", "cat", "clamp", "class", "config", "constant", "coords", "cor...
sam2_video/modeling_sam2_video.py:Sam2VideoTwoWayTransformer
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[ "LayerNorm", "ModelAttention", "ModelTwoWayAttentionBlock", "ModelTwoWayTransformer", "Module", "ModuleList", "None", "_", "__init__", "append", "attention_similarity", "attn_out", "class", "config", "def", "final_attn_token_to_image", "flatten", "for", "forward", "hidden_size"...
sam2_video/modeling_sam2_video.py:Sam2VideoMaskDecoder
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[ "Conv2d", "ConvTranspose2d", "Embedding", "GELU", "ModelFeedForward", "ModelLayerNorm", "ModelMaskDecoder", "ModelTwoWayTransformer", "Model_tokens_out", "Module", "ModuleList", "None", "True", "_", "__init__", "_dynamic_multimask_via_stability", "_get_stability_scores", "activatio...
sam2_video/modeling_sam2_video.py:get_1d_sine_pe
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[ "Model_1d_sine_pe", "arange", "cat", "cos", "def", "device", "dim", "dim_t", "dtype", "float32", "pe_dim", "pos_embed", "pos_inds", "return", "sin", "temperature", "torch", "unsqueeze" ]
sam2_video/modeling_sam2_video.py:Sam2VideoModel
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[ "AutoModel", "Cannot", "Conv2d", "Exactly", "F", "False", "Got", "Identity", "Linear", "ModelFeedForward", "ModelImageSegmentationOutput", "ModelMaskDecoder", "ModelMemoryAttention", "ModelMemoryEncoder", "ModelModel", "ModelPositionalEmbedding", "ModelPreTrainedModel", "ModelPromp...
canine/modeling_canine.py:CanineModelOutputWithPooling
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[ "ModelModelOutputWithPooling", "ModelOutput", "None", "attentions", "class", "hidden_states", "last_hidden_state", "pooler_output", "r" ]
canine/modeling_canine.py:CanineEmbeddings
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[ "Dropout", "Embedding", "Expected", "False", "HashBucketCodepointEmbedder_", "LayerNorm", "ModelEmbeddings", "Module", "None", "ValueError", "_PRIMES", "__init__", "_embed_hash_buckets", "_hash_bucket_tensors", "append", "arange", "be", "cat", "char_position_embeddings", "class...
canine/modeling_canine.py:CharactersToMolecules
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[ "ACT2FN", "Conv1d", "LayerNorm", "ModelToMolecules", "Module", "__init__", "activation", "cat", "char_encoding", "class", "cls_encoding", "config", "conv", "def", "dim", "downsampled", "downsampled_truncated", "downsampling_rate", "eps", "forward", "hidden_act", "hidden_siz...
canine/modeling_canine.py:ConvProjection
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[ "ACT2FN", "ConstantPad1d", "Dropout", "LayerNorm", "Model", "Model1d", "ModelProjection", "Module", "None", "__init__", "activation", "class", "config", "def", "dropout", "else", "eps", "final_char_seq", "final_seq_char_positions", "forward", "hidden_act", "hidden_dropout_p...
canine/modeling_canine.py:CanineSelfAttention
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[ "Dropout", "False", "Linear", "ModelSelfAttention", "Module", "None", "The", "ValueError", "_", "__init__", "a", "all_head_size", "and", "attention", "attention_head_size", "attention_mask", "attention_probs", "attention_probs_dropout_prob", "attention_scores", "batch_size", ...
canine/modeling_canine.py:CanineSelfOutput
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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" ]
canine/modeling_canine.py:CanineAttention
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[ "Check", "Expected", "False", "ModelAttention", "ModelSelfAttention", "ModelSelfOutput", "Module", "None", "ValueError", "__init__", "always_attend_to_first_position", "and", "append", "attend_from_chunk_stride", "attend_from_chunk_width", "attend_to_chunk_stride", "attend_to_chunk_w...
canine/modeling_canine.py:CanineIntermediate
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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" ]
canine/modeling_canine.py:CanineOutput
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[ "Dropout", "LayerNorm", "Linear", "ModelOutput", "Module", "__init__", "class", "config", "def", "dense", "dropout", "eps", "forward", "hidden_dropout_prob", "hidden_size", "hidden_states", "input_tensor", "intermediate_size", "layer_norm_eps", "nn", "return", "self", "su...
canine/modeling_canine.py:CanineLayer
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[ "False", "GradientCheckpointingLayer", "ModelAttention", "ModelIntermediate", "ModelLayer", "ModelOutput", "None", "__init__", "always_attend_to_first_position", "apply_chunking_to_forward", "attend_from_chunk_stride", "attend_from_chunk_width", "attend_to_chunk_stride", "attend_to_chunk_w...
canine/modeling_canine.py:CanineEncoder
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[ "BaseModelOutput", "False", "ModelEncoder", "ModelLayer", "Module", "ModuleList", "None", "True", "_", "__init__", "all_hidden_states", "all_self_attentions", "always_attend_to_first_position", "attend_from_chunk_stride", "attend_from_chunk_width", "attend_to_chunk_stride", "attend_t...
canine/modeling_canine.py:CaninePooler
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[ "Linear", "ModelPooler", "Module", "Tanh", "__init__", "activation", "class", "config", "def", "dense", "first_token_tensor", "forward", "hidden_size", "hidden_states", "nn", "pooled_output", "return", "self", "super" ]
canine/modeling_canine.py:CaninePredictionHeadTransform
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[ "ACT2FN", "LayerNorm", "Linear", "ModelPredictionHeadTransform", "Module", "__init__", "class", "config", "def", "dense", "else", "eps", "forward", "hidden_act", "hidden_size", "hidden_states", "if", "isinstance", "layer_norm_eps", "nn", "return", "self", "str", "super"...
canine/modeling_canine.py:CanineLMPredictionHead
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[ "Linear", "ModelLMPredictionHead", "ModelPredictionHeadTransform", "Module", "Parameter", "__init__", "bias", "class", "config", "decoder", "def", "forward", "hidden_size", "hidden_states", "nn", "return", "self", "super", "torch", "transform", "vocab_size", "zeros" ]
canine/modeling_canine.py:CanineOnlyMLMHead
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[ "ModelLMPredictionHead", "ModelOnlyMLMHead", "Module", "__init__", "class", "config", "def", "forward", "nn", "prediction_scores", "predictions", "return", "self", "sequence_output", "super" ]
canine/modeling_canine.py:CaninePreTrainedModel
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[ "Model", "ModelConfig", "ModelEmbeddings", "ModelPreTrainedModel", "PreTrainedModel", "True", "_init_weights", "arange", "base_model_prefix", "class", "config", "copy_", "def", "expand", "if", "init", "isinstance", "module", "position_ids", "self", "shape", "super", "supp...
canine/modeling_canine.py:CanineModel
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[ "CharactersToMolecules", "ConvProjection", "False", "MaxPool1d", "ModelEmbeddings", "ModelEncoder", "ModelModel", "ModelModelOutputWithPooling", "ModelPooler", "ModelPreTrainedModel", "None", "True", "__init__", "_create_3d_attention_mask_from_input_mask", "_downsample_attention_mask", ...
canine/modeling_canine.py:CanineForSequenceClassification
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[ "BCEWithLogitsLoss", "CrossEntropyLoss", "Dropout", "Linear", "MSELoss", "Model", "ModelForSequenceClassification", "ModelModel", "ModelPreTrainedModel", "None", "SequenceClassifierOutput", "__init__", "and", "attention_mask", "attentions", "auto_docstring", "class", "classifier", ...
canine/modeling_canine.py:CanineForMultipleChoice
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[ "CrossEntropyLoss", "Dropout", "Linear", "Model", "ModelForMultipleChoice", "ModelModel", "ModelPreTrainedModel", "MultipleChoiceModelOutput", "None", "__init__", "attention_mask", "attentions", "auto_docstring", "class", "classifier", "config", "def", "dropout", "else", "forwa...
canine/modeling_canine.py:CanineForTokenClassification
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[ "CrossEntropyLoss", "Dropout", "Linear", "Model", "ModelForTokenClassification", "ModelModel", "ModelPreTrainedModel", "None", "TokenClassifierOutput", "__init__", "attention_mask", "attentions", "auto_docstring", "class", "classifier", "config", "def", "dropout", "else", "forw...
canine/modeling_canine.py:CanineForQuestionAnswering
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[ "CrossEntropyLoss", "Linear", "Model", "ModelForQuestionAnswering", "ModelModel", "ModelPreTrainedModel", "None", "QuestionAnsweringModelOutput", "__init__", "and", "attention_mask", "attentions", "auto_docstring", "clamp_", "class", "config", "def", "dim", "else", "end_logits"...
deepseek_v3/modeling_deepseek_v3.py:DeepseekV3RMSNorm
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3RotaryEmbedding
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3MLP
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3TopkRouter
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3NaiveMoe
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3MoE
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deepseek_v3/modeling_deepseek_v3.py:rotate_half
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deepseek_v3/modeling_deepseek_v3.py:apply_rotary_pos_emb
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deepseek_v3/modeling_deepseek_v3.py:repeat_kv
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deepseek_v3/modeling_deepseek_v3.py:eager_attention_forward
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deepseek_v3/modeling_deepseek_v3.py:apply_rotary_pos_emb_interleave
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deepseek_v3/modeling_deepseek_v3.py:yarn_get_mscale
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3Attention
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3DecoderLayer
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3PreTrainedModel
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3Model
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3ForCausalLM
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3ForSequenceClassification
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deepseek_v3/modeling_deepseek_v3.py:DeepseekV3ForTokenClassification
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olmo/modeling_olmo.py:OlmoLayerNorm
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olmo/modeling_olmo.py:OlmoMLP
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olmo/modeling_olmo.py:OlmoRotaryEmbedding
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olmo/modeling_olmo.py:rotate_half
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[ "Model_half", "cat", "def", "dim", "return", "shape", "torch", "x", "x1", "x2" ]
olmo/modeling_olmo.py:repeat_kv
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olmo/modeling_olmo.py:eager_attention_forward
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olmo/modeling_olmo.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" ]
olmo/modeling_olmo.py:OlmoAttention
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olmo/modeling_olmo.py:OlmoDecoderLayer
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olmo/modeling_olmo.py:OlmoPreTrainedModel
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olmo/modeling_olmo.py:OlmoModel
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olmo/modeling_olmo.py:OlmoForCausalLM
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glm_image/modeling_glm_image.py:GlmImageVisionMLP
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glm_image/modeling_glm_image.py:repeat_kv
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glm_image/modeling_glm_image.py:eager_attention_forward
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glm_image/modeling_glm_image.py:GlmImageVisionAttention
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glm_image/modeling_glm_image.py:GlmImageVisionPatchEmbed
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glm_image/modeling_glm_image.py:GlmImageVisionEmbeddings
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glm_image/modeling_glm_image.py:GlmImageVisionBlock
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glm_image/modeling_glm_image.py:rotate_half
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[ "Model_half", "cat", "def", "dim", "return", "shape", "torch", "x", "x1", "x2" ]
glm_image/modeling_glm_image.py:apply_rotary_pos_emb
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glm_image/modeling_glm_image.py:GlmImageTextAttention
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glm_image/modeling_glm_image.py:GlmImageRMSNorm
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glm_image/modeling_glm_image.py:GlmImageTextMLP
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glm_image/modeling_glm_image.py:GlmImageTextDecoderLayer
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glm_image/modeling_glm_image.py:GlmImagePreTrainedModel
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glm_image/modeling_glm_image.py:GlmImageModelOutputWithPast
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[ "ModelModelOutputWithPast", "ModelOutput", "None", "attentions", "class", "hidden_states", "last_hidden_state", "past_key_values", "r", "rope_deltas" ]
glm_image/modeling_glm_image.py:GlmImageVQVAEVectorQuantizer
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glm_image/modeling_glm_image.py:GlmImageVQVAEModelOutput
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[ "BaseModelOutputWithPooling", "ModelVQVAEModelOutput", "None", "class", "embedding_loss", "image_tokens", "quantized_last_hidden_state", "r" ]
glm_image/modeling_glm_image.py:GlmImageVQVAE
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glm_image/modeling_glm_image.py:GlmImageVisionModel
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glm_image/modeling_glm_image.py:GlmImageTextRotaryEmbedding
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glm_image/modeling_glm_image.py:GlmImageTextModel
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glm_image/modeling_glm_image.py:GlmImageModel
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glm_image/modeling_glm_image.py:GlmImageCausalLMOutputWithPast
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[ "ModelCausalLMOutputWithPast", "ModelOutput", "None", "attentions", "class", "hidden_states", "logits", "loss", "past_key_values", "r", "rope_deltas" ]
glm_image/modeling_glm_image.py:GlmImageForConditionalGeneration
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pix2struct/modeling_pix2struct.py:Pix2StructLayerNorm
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pix2struct/modeling_pix2struct.py:Pix2StructVisionEmbeddings
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pix2struct/modeling_pix2struct.py:Pix2StructVisionAttention
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pix2struct/modeling_pix2struct.py:Pix2StructVisionMlp
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pix2struct/modeling_pix2struct.py:Pix2StructVisionLayer
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pix2struct/modeling_pix2struct.py:Pix2StructVisionEncoder
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pix2struct/modeling_pix2struct.py:Pix2StructPreTrainedModel
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pix2struct/modeling_pix2struct.py:Pix2StructVisionModel
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pix2struct/modeling_pix2struct.py:Pix2StructTextDenseGatedActDense
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[ "ACT2FN", "Dropout", "Linear", "ModelTextDenseGatedActDense", "Module", "Tensor", "__init__", "act", "and", "class", "config", "d_ff", "def", "dense_act_fn", "dropout", "dropout_rate", "dtype", "forward", "hidden_gelu", "hidden_linear", "hidden_size", "hidden_states", "if...
pix2struct/modeling_pix2struct.py:Pix2StructTextLayerFF
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[ "DenseReluDense", "Dropout", "ModelLayerNorm", "ModelTextDenseGatedActDense", "ModelTextLayerFF", "Module", "__init__", "class", "config", "def", "dropout", "dropout_rate", "eps", "forward", "forwarded_states", "hidden_size", "hidden_states", "layer_norm", "layer_norm_epsilon", ...
pix2struct/modeling_pix2struct.py:Pix2StructTextAttention
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[ "Embedding", "EncoderDecoderCache", "False", "Instantiating", "Linear", "ModelTextAttention", "Module", "None", "Please", "True", "__class__", "__init__", "__name__", "_relative_position_bucket", "a", "abs", "and", "arange", "attn_output", "attn_weights", "batch_size", "bid...
pix2struct/modeling_pix2struct.py:Pix2StructTextLayerSelfAttention
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[ "Dropout", "False", "ModelLayerNorm", "ModelTextAttention", "ModelTextLayerSelfAttention", "Module", "None", "__init__", "attention", "attention_mask", "attention_output", "cache_position", "class", "config", "def", "dropout", "dropout_rate", "eps", "forward", "has_relative_att...
pix2struct/modeling_pix2struct.py:Pix2StructTextLayerCrossAttention
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[ "Dropout", "False", "ModelLayerNorm", "ModelTextAttention", "ModelTextLayerCrossAttention", "Module", "None", "__init__", "attention", "attention_mask", "attention_output", "cache_position", "class", "config", "def", "dropout", "dropout_rate", "eps", "forward", "has_relative_at...
pix2struct/modeling_pix2struct.py:Pix2StructTextBlock
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[ "False", "GradientCheckpointingLayer", "ModelTextBlock", "ModelTextLayerCrossAttention", "ModelTextLayerFF", "ModelTextLayerSelfAttention", "None", "True", "__init__", "and", "any", "attention_mask", "attention_outputs", "cache_position", "clamp", "clamp_value", "class", "config", ...