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Intelligent_Customer_Analyzer

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• "transformers.models.bert.modeling_bert.BertIntermediate",
• "sentence_transformers.model_card.SentenceTransformerModelCardData",
• "sentence_transformers.models.Transformer.Transformer",
• "transformers.models.bert.modeling_bert.BertSdpaSelfAttention",
• "transformers.models.bert.modeling_bert.BertEncoder",
• "transformers.models.bert.modeling_bert.BertAttention",
• "torch.nn.modules.linear.Linear",
• "bertopic.vectorizers._ctfidf.ClassTfidfTransformer",
• "collections.OrderedDict",
• "torch.nn.modules.container.ModuleList",
• "numpy.int64",
• "transformers.activations.GELUActivation",
• "scipy.sparse._csr.csr_matrix",
• "torch.nn.modules.normalization.LayerNorm",
• "tokenizers.AddedToken",
• "torch.nn.modules.activation.Tanh",
• "torch.nn.modules.dropout.Dropout",
• "numpy.ndarray",
• "tokenizers.Tokenizer",
• "transformers.models.bert.modeling_bert.BertEmbeddings",
• "sentence_transformers.SentenceTransformer.SentenceTransformer",
• "joblib.numpy_pickle.NumpyArrayWrapper",
• "torch._C._nn.gelu",
• "transformers.models.bert.modeling_bert.BertPooler",
• "torch.storage._load_from_bytes",
• "transformers.models.bert.modeling_bert.BertLayer",
• "transformers.models.bert.tokenization_bert_fast.BertTokenizerFast",
• "tokenizers.models.Model",
• "torch._utils._rebuild_parameter",
• "bertopic._bertopic.BERTopic",
• "bertopic.backend._sentencetransformers.SentenceTransformerBackend",
• "torch._utils._rebuild_tensor_v2",
• "sentence_transformers.models.Pooling.Pooling",
• "sklearn.feature_extraction.text.CountVectorizer",
• "sentence_transformers.models.Normalize.Normalize",
• "torch.torch_version.TorchVersion",
• "transformers.models.bert.modeling_bert.BertOutput",
• "torch.nn.modules.sparse.Embedding",
• "transformers.models.bert.modeling_bert.BertSelfOutput",
• "transformers.models.bert.configuration_bert.BertConfig",
• "numpy.dtype",
• "transformers.models.bert.modeling_bert.BertModel"

How to fix it?

• "torch._C._nn.gelu",
• "transformers.models.bert.tokenization_bert_fast.BertTokenizerFast",
• "transformers.models.bert.modeling_bert.BertSelfOutput",
• "torch._utils._rebuild_tensor_v2",
• "collections.OrderedDict",
• "numpy.ndarray",
• "torch.nn.modules.activation.Tanh",
• "sklearn.feature_extraction.text.CountVectorizer",
• "bertopic.vectorizers._ctfidf.ClassTfidfTransformer",
• "sentence_transformers.models.Pooling.Pooling",
• "torch.nn.modules.sparse.Embedding",
• "torch.nn.modules.container.ModuleList",
• "tokenizers.Tokenizer",
• "transformers.models.bert.modeling_bert.BertSdpaSelfAttention",
• "tokenizers.AddedToken",
• "torch.nn.modules.linear.Linear",
• "transformers.models.bert.configuration_bert.BertConfig",
• "transformers.models.bert.modeling_bert.BertEmbeddings",
• "numpy.dtype",
• "transformers.models.bert.modeling_bert.BertAttention",
• "transformers.activations.GELUActivation",
• "transformers.models.bert.modeling_bert.BertPooler",
• "scipy.sparse._csr.csr_matrix",
• "transformers.models.bert.modeling_bert.BertOutput",
• "transformers.models.bert.modeling_bert.BertIntermediate",
• "torch.nn.modules.normalization.LayerNorm",
• "numpy.int64",
• "torch.nn.modules.dropout.Dropout",
• "sentence_transformers.model_card.SentenceTransformerModelCardData",
• "torch._utils._rebuild_parameter",
• "joblib.numpy_pickle.NumpyArrayWrapper",
• "torch.torch_version.TorchVersion",
• "bertopic._bertopic.BERTopic",
• "transformers.models.bert.modeling_bert.BertModel",
• "sentence_transformers.models.Transformer.Transformer",
• "transformers.models.bert.modeling_bert.BertLayer",
• "torch.storage._load_from_bytes",
• "bertopic.backend._sentencetransformers.SentenceTransformerBackend",
• "sentence_transformers.SentenceTransformer.SentenceTransformer",
• "transformers.models.bert.modeling_bert.BertEncoder",
• "tokenizers.models.Model"

How to fix it?