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llamamodel: fix embedding crash for >512 tokens after #2310 #2383

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merged 1 commit into from
May 29, 2024

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n_ubatch defaults to 512, but as of the latest llama.cpp you cannot pass more than n_ubatch tokens to BERT without hitting an assertion failure.

Tested with this python code:

from gpt4all import Embed4All
m = Embed4All('nomic-embed-text-v1.f16.gguf')
e = m.embed('a ' * 513)

Without this PR, it crashes with an assertion failure (including in release builds, since it's a GGML_ASSERT). With this PR, it succeeds.

Broken by #2310 because of ggerganov/llama.cpp#6017
Fix based on ggerganov/llama.cpp#6296
Fixes #2375

n_ubatch defaults to 512, but as of the latest llama.cpp you cannot pass
more than n_ubatch tokens to the embedding model without hitting an
assertion failure.

Signed-off-by: Jared Van Bortel <[email protected]>
@cebtenzzre cebtenzzre requested a review from manyoso May 28, 2024 18:59
@cebtenzzre cebtenzzre merged commit e94177e into main May 29, 2024
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llama.cpp assertion fails: "non-causal attention requires n_ubatch >= n_tokens"
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