neuro-symbolic-ai

/

def-optimus

like 0

• "cloudpickle.cloudpickle._make_function",
• "transformers.generation.configuration_utils.GenerationConfig",
• "torch._utils._rebuild_tensor_v2",
• "torch.storage._load_from_bytes",
• "transformers.models.auto.tokenization_auto.AutoTokenizer",
• "transformers.pytorch_utils.Conv1D",
• "torch.float32",
• "torch.nn.modules.dropout.Dropout",
• "transformers.models.gpt2.configuration_gpt2.GPT2Config",
• "cloudpickle.cloudpickle_fast._function_setstate",
• "torch.nn.modules.sparse.Embedding",
• "torch.Tensor",
• "transformers.models.gpt2.modeling_gpt2.GPT2Model",
• "transformers.models.auto.modeling_auto.AutoModelForCausalLM",
• "builtins.int",
• "transformers.models.gpt2.modeling_gpt2.GPT2Attention",
• "transformers.models.gpt2.modeling_gpt2.GPT2LMHeadModel",
• "torch.Size",
• "pythae.models.nn.base_architectures.BaseDecoder",
• "cloudpickle.cloudpickle._make_skeleton_class",
• "transformers.models.gpt2.modeling_gpt2.GPT2MLP",
• "torch._utils._rebuild_parameter",
• "cloudpickle.cloudpickle.subimport",
• "builtins.str",
• "collections.OrderedDict",
• "transformers.activations.NewGELUActivation",
• "transformers.models.gpt2.tokenization_gpt2_fast.GPT2TokenizerFast",
• "torch.nn.modules.container.ModuleList",
• "tokenizers.models.Model",
• "builtins.type",
• "torch.nn.modules.linear.Linear",
• "pythae.models.base.base_utils.ModelOutput",
• "builtins.bool",
• "cloudpickle.cloudpickle._builtin_type",
• "tokenizers.Tokenizer",
• "transformers.models.gpt2.modeling_gpt2.GPT2Block",
• "torch.nn.modules.normalization.LayerNorm",
• "cloudpickle.cloudpickle_fast._class_setstate"

How to fix it?

• "pythae.models.nn.base_architectures.BaseEncoder",
• "transformers.models.bert.modeling_bert.BertModel",
• "transformers.models.bert.modeling_bert.BertSelfOutput",
• "cloudpickle.cloudpickle._builtin_type",
• "cloudpickle.cloudpickle_fast._class_setstate",
• "transformers.models.bert.modeling_bert.BertIntermediate",
• "transformers.models.bert.tokenization_bert_fast.BertTokenizerFast",
• "transformers.tokenization_utils.PreTrainedTokenizer",
• "transformers.models.auto.tokenization_auto.AutoTokenizer",
• "collections.OrderedDict",
• "builtins.int",
• "torch.storage._load_from_bytes",
• "transformers.models.bert.modeling_bert.BertAttention",
• "builtins.type",
• "torch._C._nn.gelu",
• "pythae.models.base.base_utils.ModelOutput",
• "transformers.models.bert.modeling_bert.BertPooler",
• "cloudpickle.cloudpickle._make_skeleton_class",
• "cloudpickle.cloudpickle_fast._function_setstate",
• "torch.nn.modules.container.ModuleList",
• "transformers.models.bert.configuration_bert.BertConfig",
• "torch.nn.modules.sparse.Embedding",
• "transformers.models.bert.modeling_bert.BertSelfAttention",
• "transformers.models.auto.modeling_auto.AutoModel",
• "transformers.models.bert.modeling_bert.BertOutput",
• "cloudpickle.cloudpickle.subimport",
• "torch.nn.modules.linear.Linear",
• "torch._utils._rebuild_parameter",
• "cloudpickle.cloudpickle._make_function",
• "tokenizers.Tokenizer",
• "torch.Tensor",
• "torch.nn.modules.dropout.Dropout",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.activation.Tanh",
• "torch.nn.modules.normalization.LayerNorm",
• "transformers.models.bert.modeling_bert.BertEmbeddings",
• "transformers.models.bert.modeling_bert.BertEncoder",
• "transformers.models.bert.modeling_bert.BertLayer",
• "builtins.str",
• "transformers.models.gpt2.tokenization_gpt2_fast.GPT2TokenizerFast",
• "tokenizers.models.Model",
• "transformers.activations.GELUActivation"

How to fix it?