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RuntimeError: stack expects each tensor to be equal size, but got [n, 768] at entry 0 and [m, 768] at entry 1
See original GitHub issueHi,
I was using the ‘token_embeddings’ feature of the sentence transformers and ran into this error. I have passed a list of sentences to the model.encode() for generating token_embeddings. Are the sentences not being padded before getting converted into token_embeddings? Can you suggest a workaround to this?
b_emb = model.encode(arr[i : i + batch_size], output_value='token_embeddings', convert_to_tensor=True, is_pretokenized=True, show_progress_bar=False)
This is the exact code I am using.
Thanks
Issue Analytics
- State:
- Created 3 years ago
- Comments:7 (1 by maintainers)
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Yes, it is working now. Thank you! @jicksonp
@nandinib1999 You can fix the error by changing below line
b_emb = model.encode(arr[i : i + batch_size], output_value='token_embeddings', convert_to_tensor=True, is_pretokenized=True, show_progress_bar=False)with
b_emb = model.encode(arr[i: i + batch_size], output_value='token_embeddings', convert_to_tensor=True, is_pretokenized=True, show_progress_bar=False, batch_size=batch_size)