Wipiii

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Semantic

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• "torch.nn.modules.dropout.Dropout",
• "numpy.ndarray",
• "pandas._libs.internals._unpickle_block",
• "torch.nn.modules.sparse.Embedding",
• "sentence_transformers.models.Normalize.Normalize",
• "__main__.Preprocessor",
• "torch._utils._rebuild_tensor_v2",
• "pandas.core.indexes.range.RangeIndex",
• "transformers.models.mpnet.modeling_mpnet.MPNetPooler",
• "transformers.models.mpnet.modeling_mpnet.MPNetSelfAttention",
• "torch.torch_version.TorchVersion",
• "pandas.core.internals.managers.BlockManager",
• "torch.storage._load_from_bytes",
• "torch.nn.modules.linear.Linear",
• "pandas.core.indexes.base.Index",
• "transformers.models.mpnet.tokenization_mpnet_fast.MPNetTokenizerFast",
• "torch.nn.modules.container.ModuleList",
• "transformers.models.mpnet.modeling_mpnet.MPNetEmbeddings",
• "nltk.stem.porter.PorterStemmer",
• "sentence_transformers.SentenceTransformer.SentenceTransformer",
• "transformers.models.mpnet.modeling_mpnet.MPNetModel",
• "__main__.SBERTModel",
• "builtins.slice",
• "tokenizers.models.Model",
• "sentence_transformers.models.Transformer.Transformer",
• "transformers.models.mpnet.modeling_mpnet.MPNetEncoder",
• "pandas.core.indexes.base._new_Index",
• "torch.nn.modules.normalization.LayerNorm",
• "transformers.models.mpnet.modeling_mpnet.MPNetIntermediate",
• "torch._utils._rebuild_parameter",
• "transformers.activations.GELUActivation",
• "torch._C._nn.gelu",
• "sentence_transformers.models.Pooling.Pooling",
• "torch.nn.modules.activation.Tanh",
• "pandas.core.frame.DataFrame",
• "numpy.core.multiarray._reconstruct",
• "tokenizers.Tokenizer",
• "tokenizers.AddedToken",
• "transformers.models.mpnet.modeling_mpnet.MPNetAttention",
• "transformers.models.mpnet.modeling_mpnet.MPNetLayer",
• "transformers.models.mpnet.modeling_mpnet.MPNetOutput",
• "sentence_transformers.model_card.SentenceTransformerModelCardData",
• "collections.OrderedDict",
• "numpy.dtype",
• "transformers.models.mpnet.configuration_mpnet.MPNetConfig"

How to fix it?

• "sentence_transformers.models.Pooling.Pooling",
• "transformers.models.bert.modeling_bert.BertSelfOutput",
• "pandas.core.indexes.range.RangeIndex",
• "transformers.models.bert.modeling_bert.BertOutput",
• "pandas.core.indexes.base._new_Index",
• "transformers.models.bert.modeling_bert.BertSelfAttention",
• "transformers.models.bert.modeling_bert.BertModel",
• "torch.nn.modules.sparse.Embedding",
• "transformers.models.bert.tokenization_bert_fast.BertTokenizerFast",
• "numpy.ndarray",
• "numpy.core.multiarray._reconstruct",
• "transformers.models.bert.modeling_bert.BertIntermediate",
• "sentence_transformers.model_card.SentenceTransformerModelCardData",
• "transformers.models.bert.modeling_bert.BertPooler",
• "numpy.dtype",
• "torch.nn.modules.dropout.Dropout",
• "pandas._libs.internals._unpickle_block",
• "pandas.core.internals.managers.BlockManager",
• "transformers.models.bert.modeling_bert.BertAttention",
• "tokenizers.models.Model",
• "torch.nn.modules.linear.Linear",
• "nltk.stem.porter.PorterStemmer",
• "torch.nn.modules.activation.Tanh",
• "transformers.models.bert.configuration_bert.BertConfig",
• "pandas.core.indexes.base.Index",
• "pandas.core.frame.DataFrame",
• "transformers.models.bert.modeling_bert.BertEmbeddings",
• "torch.nn.modules.normalization.LayerNorm",
• "transformers.models.bert.modeling_bert.BertEncoder",
• "sentence_transformers.models.Transformer.Transformer",
• "transformers.activations.GELUActivation",
• "torch.nn.modules.container.ModuleList",
• "sentence_transformers.SentenceTransformer.SentenceTransformer",
• "torch.torch_version.TorchVersion",
• "torch._utils._rebuild_tensor_v2",
• "torch._utils._rebuild_parameter",
• "torch._C._nn.gelu",
• "sentence_transformers.models.Normalize.Normalize",
• "tokenizers.Tokenizer",
• "transformers.models.bert.modeling_bert.BertLayer",
• "__main__.SBERTModel",
• "torch.storage._load_from_bytes",
• "tokenizers.AddedToken",
• "__main__.Preprocessor",
• "collections.OrderedDict"

How to fix it?