Can we resize embedding with embedding weighted initialized differently??
# ❓ Questions & Help


When we add new tokens, this method automatically adds embedding using torch nn.Embedding. 
https://huggingface.co/transformers/_modules/transformers/modeling_utils.html#PreTrainedModel.resize_token_embeddings

The documentation says the resized embeddings are nn. Embedding, which said they by default initialize weights from N(0, 1) (https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html). But I have checked that the resized embedding weights are almost N(0, 0.01) or N(0, 0.02)? Can I check **the true distribution of resized embedding weights** ?

## If I want the embedding weights initialized differently, how can I achieve that efficiently?

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**A link to original question on the forum/Stack Overflow**:
One way is to use `config.initializer_range`

#6562<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
