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Duplicated from  hwchase17/chat-langchain

huggingface

/

transformers-chat

like 39

Runtime error

• "InstructorEmbedding.instructor.INSTRUCTOR",
• "langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings",
• "torch.nn.modules.activation.ReLU",
• "transformers.models.t5.modeling_t5.T5Block",
• "torch.nn.modules.dropout.Dropout",
• "transformers.models.t5.modeling_t5.T5LayerSelfAttention",
• "torch.float32",
• "collections.OrderedDict",
• "InstructorEmbedding.instructor.INSTRUCTOR_Pooling",
• "torch._utils._rebuild_parameter",
• "InstructorEmbedding.instructor.INSTRUCTOR_Transformer",
• "langchain.vectorstores.faiss.FAISS",
• "tokenizers.Tokenizer",
• "tokenizers.models.Model",
• "torch.nn.modules.linear.Linear",
• "transformers.models.t5.modeling_t5.T5LayerFF",
• "sentence_transformers.models.Dense.Dense",
• "sentence_transformers.models.Normalize.Normalize",
• "transformers.models.t5.tokenization_t5_fast.T5TokenizerFast",
• "torch.nn.modules.sparse.Embedding",
• "transformers.models.t5.modeling_t5.T5LayerNorm",
• "torch.nn.modules.linear.Identity",
• "langchain.docstore.in_memory.InMemoryDocstore",
• "transformers.models.t5.modeling_t5.T5EncoderModel",
• "langchain.docstore.document.Document",
• "torch.nn.modules.container.ModuleList",
• "transformers.models.t5.modeling_t5.T5Stack",
• "transformers.models.t5.modeling_t5.T5DenseReluDense",
• "torch.device",
• "transformers.models.t5.modeling_t5.T5Attention",
• "transformers.models.t5.configuration_t5.T5Config",
• "torch._utils._rebuild_tensor_v2",
• "builtins.getattr",
• "torch.storage._load_from_bytes",
• "faiss.swigfaiss.IndexFlatL2"

How to fix it?

• "InstructorEmbedding.instructor.INSTRUCTOR",
• "langchain.embeddings.huggingface.HuggingFaceInstructEmbeddings",
• "torch.nn.modules.activation.ReLU",
• "transformers.models.t5.modeling_t5.T5Block",
• "torch.nn.modules.dropout.Dropout",
• "transformers.models.t5.modeling_t5.T5LayerSelfAttention",
• "torch.float32",
• "collections.OrderedDict",
• "InstructorEmbedding.instructor.INSTRUCTOR_Pooling",
• "torch._utils._rebuild_parameter",
• "InstructorEmbedding.instructor.INSTRUCTOR_Transformer",
• "langchain.vectorstores.faiss.FAISS",
• "tokenizers.Tokenizer",
• "tokenizers.models.Model",
• "torch.nn.modules.linear.Linear",
• "transformers.models.t5.modeling_t5.T5LayerFF",
• "sentence_transformers.models.Dense.Dense",
• "sentence_transformers.models.Normalize.Normalize",
• "transformers.models.t5.tokenization_t5_fast.T5TokenizerFast",
• "torch.nn.modules.sparse.Embedding",
• "transformers.models.t5.modeling_t5.T5LayerNorm",
• "torch.nn.modules.linear.Identity",
• "langchain.docstore.in_memory.InMemoryDocstore",
• "langchain.prompts.example_selector.semantic_similarity.SemanticSimilarityExampleSelector",
• "transformers.models.t5.modeling_t5.T5EncoderModel",
• "langchain.docstore.document.Document",
• "torch.nn.modules.container.ModuleList",
• "transformers.models.t5.modeling_t5.T5Stack",
• "transformers.models.t5.modeling_t5.T5DenseReluDense",
• "torch.device",
• "transformers.models.t5.modeling_t5.T5Attention",
• "transformers.models.t5.configuration_t5.T5Config",
• "torch._utils._rebuild_tensor_v2",
• "builtins.getattr",
• "torch.storage._load_from_bytes",
• "faiss.swigfaiss.IndexFlatL2"

How to fix it?