Streamline embeddings from "non-embedding" models #8087
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ggerganov
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Jun 24, 2024
llama.cpp
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| @@ -12618,14 +12618,15 @@ static int llama_decode_internal( | |||
| std::vector<llama_seq_id *> seq_id_arr; | |||
| std::vector<std::vector<llama_seq_id>> seq_id; | |||
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| // this indicates we are doing pooled embedding, so we ignore batch.logits and output all tokens | |||
| bool embed_pooled = cparams.embeddings && cparams.pooling_type != LLAMA_POOLING_TYPE_NONE; | |||
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Naming this embd_pooled seems more inline with the usage of the embd identifier in llama.cpp:
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| bool embed_pooled = cparams.embeddings && cparams.pooling_type != LLAMA_POOLING_TYPE_NONE; | |
| const bool embd_pooled = cparams.embeddings && cparams.pooling_type != LLAMA_POOLING_TYPE_NONE; |
mofosyne
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compilade
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Jun 24, 2024
ggerganov
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Jun 25, 2024
|
@compilade cool! just rebased to master |
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The goal here is to get the big embedding models at the top of the MTEB leaderboard working. There are two changes:
batch.logitsis fully ignored for pooled embeddings.attention_typetollama_contex_paramsthat allows for causal, non-causal, or unspecified (model default).With this PR, we can get accurate results (matching HF) from at least the number 2 spot
gte-Qwen2-7B-instruct. For instance, with the command:./llama-embedding -m gte-qwen2-7b-instruct-f16.gguf -p "hello world" -ngl 99 --pooling last --at tention non-causal -c 512