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feat: add changes to handle jina v2 base code #7596

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merged 10 commits into from
Jun 6, 2024

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JoanFM
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@JoanFM JoanFM commented May 28, 2024

PR to allow using jinaai/jina-embeddings-v2-base-code with llama.cpp. It has an extra normalization layer compared to other models of the JinaV2 family and this is why it is considered independently.

@github-actions github-actions bot added the python python script changes label May 28, 2024
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github-actions bot commented May 28, 2024

📈 llama.cpp server for bench-server-baseline on Standard_NC4as_T4_v3 for phi-2-q4_0: 527 iterations 🚀

Expand details for performance related PR only
  • Concurrent users: 8, duration: 10m
  • HTTP request : avg=8891.02ms p(95)=21954.48ms fails=, finish reason: stop=474 truncated=53
  • Prompt processing (pp): avg=104.81tk/s p(95)=444.45tk/s
  • Token generation (tg): avg=45.37tk/s p(95)=46.03tk/s
  • ggml-org/models/phi-2/ggml-model-q4_0.gguf parallel=8 ctx-size=16384 ngl=33 batch-size=2048 ubatch-size=256 pp=1024 pp+tg=2048 branch=feat-jina-v2-base-code commit=4c4d877d23dd27fc7e323b4a2623db825e8bd29f

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@mofosyne mofosyne added the Review Complexity : Medium Generally require more time to grok but manageable by beginner to medium expertise level label May 29, 2024
@teleprint-me
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teleprint-me commented May 31, 2024

It's how the tokens are handled in llama.cpp. I'm in the middle of figuring out how tokenizers operates under the hood and seeing if there's a way to create a bridge between the two. Actually, your input would be invaluable (#7379). Or if you know someone that's better suited and has a deeper understanding of tokenizers (e.g. BPE/WPM) in general. I'm interested in Jina because the english version uses WPM. The spanish and dutch versions use BPE. I'm more focused on Llama-2 and Llama-3 for BPE.

Aside: I have no idea how the CD/CI is setup here. I have some experience with Jenkins, but all of this is outside of the scope of what I'm focused on. Also, I'm just a contributor. I just chime in when I think I might have something of value to add.

@JoanFM
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JoanFM commented Jun 4, 2024

It's how the tokens are handled in llama.cpp. I'm in the middle of figuring out how tokenizers operates under the hood and seeing if there's a way to create a bridge between the two. Actually, your input would be invaluable (#7379). Or if you know someone that's better suited and has a deeper understanding of tokenizers (e.g. BPE/WPM) in general. I'm interested in Jina because the english version uses WPM. The spanish and dutch versions use BPE. I'm more focused on Llama-2 and Llama-3 for BPE.

Aside: I have no idea how the CD/CI is setup here. I have some experience with Jenkins, but all of this is outside of the scope of what I'm focused on. Also, I'm just a contributor. I just chime in when I think I might have something of value to add.

Hey @teleprint-me ,

To be honest, I found it quite hard to work with tokenizer logic here, but I do not quite understand what you aim to achieve in #7379. If you want we can jump in a call to discuss and make this process more agile.

@ggerganov
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could you also guide me on how to fix the CI problems?

Rebase on latest master and the CI should work

@JoanFM
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JoanFM commented Jun 4, 2024

could you also guide me on how to fix the CI problems?

Rebase on latest master and the CI should work

I will, thanks

@ggerganov
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So ):\ tit should not be matched. Is there any logic in the code that eliminates these patterns \ from the vocab?

Hm, not sure why this happens. We don't escape strings in the vocab - only in the prompt input:

llama.cpp/common/common.cpp

Lines 249 to 257 in 3b38d48

if (params.escape) {
string_process_escapes(params.prompt);
string_process_escapes(params.input_prefix);
string_process_escapes(params.input_suffix);
string_process_escapes(sparams.cfg_negative_prompt);
for (auto & antiprompt : params.antiprompt) {
string_process_escapes(antiprompt);
}
}

@JoanFM
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JoanFM commented Jun 4, 2024

So ):\ tit should not be matched. Is there any logic in the code that eliminates these patterns \ from the vocab?

Hm, not sure why this happens. We don't escape strings in the vocab - only in the prompt input:

llama.cpp/common/common.cpp

Lines 249 to 257 in 3b38d48

if (params.escape) {
string_process_escapes(params.prompt);
string_process_escapes(params.input_prefix);
string_process_escapes(params.input_suffix);
string_process_escapes(sparams.cfg_negative_prompt);
for (auto & antiprompt : params.antiprompt) {
string_process_escapes(antiprompt);
}
}

I will try to investigate this

@JoanFM
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JoanFM commented Jun 4, 2024

@ggerganov,

I am also trying to see if I can add support for chinese model and I manage to get it to work for English, but not for the Chinese characters. Is there a supported model in Chinese? So I can see if I can inspire on which tokenizers they use, etc ...?

@ggerganov
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I believe the most recent model that we added and also supports Chinese is https://huggingface.co/deepseek-ai/DeepSeek-V2. See if @fairydreaming's PR could be of any help: #7519

@JoanFM
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JoanFM commented Jun 4, 2024

Hey @ggerganov ,

I am starting to think that it is not a problem of the tokenizer.

Here is my observation.

I am tryng to run this code to check how the embedding behaves:

gdb --args ../build/bin/embedding -m ./jina-embeddings-v2-base-code.gguf --threads 1 --verbose-prompt -p "for idx, x in enumerate(xs):\n    print(idx, x)"

and this is what gdb is telling me:

(gdb) run
Starting program: /home/joan/workspace/ollama/llm/llama.cpp/build/bin/embedding -m ./jina-embeddings-v2-base-code.gguf --threads 1 --verbose-prompt -p for\ idx,\ x\ in\ enumerate\(xs\):\\n\ \ \ \ print\(idx,\ x\)

Look at all the \ that have been added. This seems to be the reason why I get different tokenization, in Python If I add an extra \ before \\n I get the same encoding.

I am not sure if it is a problem of how the standard input is encoded or something? Do you happen to have any clue about this?

if I hardcode this sentence and avoid the split lines.

params.prompt = "for idx, x in enumerate(xs):\n    print(idx, x)";

I get the same behavior as in Python

@ggerganov
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I see, does adding -e to the command-line argument fix the issue?

 ../build/bin/embedding -m ./jina-embeddings-v2-base-code.gguf --threads 1 --verbose-prompt -e -p "for idx, x in enumerate(xs):\n    print(idx, x)"

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JoanFM commented Jun 4, 2024

I see, does adding -e to the command-line argument fix the issue?

 ../build/bin/embedding -m ./jina-embeddings-v2-base-code.gguf --threads 1 --verbose-prompt -e -p "for idx, x in enumerate(xs):\n    print(idx, x)"

Oh, it does!

@JoanFM JoanFM marked this pull request as ready for review June 4, 2024 15:02
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JoanFM commented Jun 5, 2024

I see, does adding -e to the command-line argument fix the issue?

 ../build/bin/embedding -m ./jina-embeddings-v2-base-code.gguf --threads 1 --verbose-prompt -e -p "for idx, x in enumerate(xs):\n    print(idx, x)"

@ggerganov ,

how then can we be sure this behavior is available in the server? I see this escape option only available in the example itself.

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I believe server already escapes these through the JSON parsing library. Btw all examples now escape by default since #7675, so no need to even add -e explicitly

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JoanFM commented Jun 5, 2024

Hey @ggerganov,

Is there something from my code that may have caused this CI to fail?

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Probably just a fluke, will restart the workflows now

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JoanFM commented Jun 6, 2024

@ggerganov I tested the behavior in server and works, I consider this is ready to be reviewed.

@ggerganov ggerganov merged commit f5d7b26 into ggerganov:master Jun 6, 2024
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4 participants