A small repro would be great. Currently can you try setting the qconfig for the embedding module to float_qparams_weight_only_qconfig? We only support float qparams quantization for the Embedding layers. If you use the default qconfig for Embedding layers, you may run into this error.
Small example to demonstrate this
class EmbeddingWithLinear(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.emb = torch.nn.Embedding(num_embeddings=10, embedding_dim=12)
        self.fc = torch.nn.Linear(5, 5)
        self.emb.qconfig = float_qparams_weight_only_qconfig
        self.qconfig = default_qconfig

    def forward(self, indices, linear_in):
        return self.emb(indices), self.fc(linear_in)