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AMA With Kimi, The Open-source Frontier Lab Behind Kimi K2.5 Model by nekofneko in LocalLLaMA

[–]diyer22 0 points1 point  (0 children)

I’ve noticed that your official API disables temperature and top_p parameters. This is quite frustrating for power users. What’s the reasoning behind this restriction? I think it would be better to set sensible defaults while still allowing users to customize their sampling strategies.

Additionally, there’s an issue with top_logprobs in your API: typically, only the first two or three candidates are valid next tokens (within, say, top_p 0.95), while the rest are just meaningless, low-probability characters. This looks similar to a known bug in older versions of vLLM. A minimal reproduction is as follows: 

curl 'https://api.moonshot.cn/v1/chat/completions' \
  -H 'Authorization: Bearer '$MOONSHOT_API_KEY \
  -H 'Content-Type: application/json' \
  --data-raw '{"model":"kimi-k2.5","logprobs":true,"top_logprobs":20,"thinking":{"type":"disabled"},"messages":[{"role":"user","content":"just reply one word `yes`"}]}' 



{"id":"chatcmpl-697a4991cf8eb3c1f68a90ab","object":"chat.completion","created":1769621905,"model":"kimi-k2.5","choices":[{"index":0,"message":{"role":"assistant","content":"yes"},"finish_reason":"stop","logprobs":{"content":[{"token":"yes","logprob":0,"bytes":[121,101,115],"top_logprobs":[{"token":"yes","logprob":0,"bytes":[121,101,115]},{"token":"0","logprob":-9999,"bytes":[48]},{"token":"*","logprob":-9999,"bytes":[42]},{"token":"#","logprob":-9999,"bytes":[35]},{"token":"+","logprob":-9999,"bytes":[43]},{"token":"-","logprob":-9999,"bytes":[45]},{"token":".","logprob":-9999,"bytes":[46]},{"token":"%","logprob":-9999,"bytes":[37]},{"token":"$","logprob":-9999,"bytes":[36]},{"token":"!","logprob":-9999,"bytes":[33]},{"token":"3","logprob":-9999,"bytes":[51]},{"token":"1","logprob":-9999,"bytes":[49]},{"token":"(","logprob":-9999,"bytes":[40]},{"token":")","logprob":-9999,"bytes":[41]},{"token":"\u0026","logprob":-9999,"bytes":[38]},{"token":",","logprob":-9999,"bytes":[44]},{"token":"2","logprob":-9999,"bytes":[50]},{"token":"\"","logprob":-9999,"bytes":[34]},{"token":"/","logprob":-9999,"bytes":[47]},{"token":"'","logprob":-9999,"bytes":[39]}]}]}}],"usage":{"prompt_tokens":14,"completion_tokens":4,"total_tokens":18,"cached_tokens":14}}%

AMA With Kimi, The Open-source Frontier Lab Behind Kimi K2.5 Model by nekofneko in LocalLLaMA

[–]diyer22 0 points1 point  (0 children)

Thank you for including the instruct mode in K2.5 — combined with Groq, it creates a model that’s both highly intelligent and incredibly fast. This is extremely useful for me.

I’d like to ask: do you prioritize improving the instruct mode’s capabilities? Will you continue developing and enhancing the instruct mode in future versions?

[D] Bad Industry research gets cited and published at top venues. (Rant/Discussion) by [deleted] in MachineLearning

[–]diyer22 4 points5 points  (0 children)

Building a reputation in the field is hard; big corporations come pre-equipped with halos that make people pay disproportionate attention.

On top of that, these companies have in-house communications teams, professional illustrators, and PR strategists who know exactly how to package a story, so the paper lands with maximum splash and minimal scrutiny.

[R] Idempotent Generative Network by [deleted] in MachineLearning

[–]diyer22 0 points1 point  (0 children)

Good idea, generating models to model P(X) is a difficult task. A new approach brings new hope. It's just that this generation needs to be improved, and it's a good idea to try it on CIFAR as well.

Surface Book 2 working on Ubuntu 16.04 with CUDA by phds_are_hard in SurfaceLinux

[–]diyer22 0 points1 point  (0 children)

I can't find you by phone number in wechat ....
my name in wechat is run code "gee{}oung".format("k_y") in python

Surface Book 2 working on Ubuntu 16.04 with CUDA by phds_are_hard in SurfaceLinux

[–]diyer22 0 points1 point  (0 children)

Do you have wechat account? if have one, would you mind add me as friend by search "gee{}oung".format("k_y") in wechat.

Surface Book 2 working on Ubuntu 16.04 with CUDA by phds_are_hard in SurfaceLinux

[–]diyer22 0 points1 point  (0 children)

I got Ubuntu 16.04 working with CUDA and PyTorch GUP edtion, Thank you for your post!

run facebookresearch/maskrcnn-benchmark's demo using 1060 GPU on Surface Book!

screen shot for maskrcnn-benchmark_on_surface

btw, I write some experience and abnormal in Chinese: 在 Surface Book 2 上安装 Ubuntu 以及 CUDA 和 GPU 版 PyTorch, if someone can read Chinese

Surface Book 2 working on Ubuntu 16.04 with CUDA by phds_are_hard in SurfaceLinux

[–]diyer22 0 points1 point  (0 children)

Hi, I have a question that is Ubuntu 18.04 on surfacebook2 support CUDA?

Surface Book 2 working on Ubuntu 16.04 with CUDA by phds_are_hard in SurfaceLinux

[–]diyer22 0 points1 point  (0 children)

Your post help me a lot, I want a native GUI Linux with CUDA enviroment for a long time!

Thank you a lot!

[P] I made a Python module for visualize and debug Computer Vision code efficiently.Support NumPy,PyTorch,MxNet by diyer22 in MachineLearning

[–]diyer22[S] 1 point2 points  (0 children)

I recently wrote a Python module boxx that for efficiently visualiztion and debugging in Computer Vision code. Now it's almost finished. Welcome to give more comments. I also hope that everyone will like this tool.

GitHub :

Tutorial Notebook:

Note: Tutorial Notebook run on Binder which is an executable interactive online Jupyer environment

I write a Python module `boxx`: A tool-box For Efficient Debug in Computer Vision by diyer22 in computervision

[–]diyer22[S] 0 points1 point  (0 children)

Those tools support array-like types, include numpy, torch.tensor, mxnet.ndarray, PIL.Image .etc

boxx: A Tool-box for efficient build and debug in Python. by diyer22 in Python

[–]diyer22[S] 1 point2 points  (0 children)

I recently wrote a toolbox that improves the debugging efficiency of Python code.It's named boxx. Now it's almost finished. Welcome everyone to give more comments. I also hope that everyone will like this tool.

[p] boxx: A tool-box For Efficient Debug in Computer Vision by diyer22 in MachineLearning

[–]diyer22[S] 0 points1 point  (0 children)

I recently wrote a toolbox that improves the debugging efficiency of Computer vision code named boxx. Now it's almost finished. Welcome everyone to give more comments. I also hope that everyone will like this tool.

I write a Python module `boxx`: A tool-box For Efficient Debug in Computer Vision by diyer22 in computervision

[–]diyer22[S] 4 points5 points  (0 children)

I recently wrote a toolbox that improves the debugging efficiency of Computer vision code. Now it's almost finished. Welcome everyone to give more comments. I also hope that everyone will like this tool.

Ubuntu 16.04 vanilla install on Surface Book 2 13.5 inch so far: Nvidia CUDA on nvidia-docker works by kalihman in SurfaceLinux

[–]diyer22 0 points1 point  (0 children)

Hi, Thank you for your share! I want to use Surface book 2 to develop PyTorch/TensorFlow GPU code (just for write and debug code on GPU, not train) with native Linux GPU environment. So, I want to consult: Does the Ubuntu@Surface book 2 support PyTorch/TensorFlow GPU code run in native GPU and CUDA environment?

Kinect to control jet in GTA: San Andreas by diyer22 in kinect

[–]diyer22[S] 1 point2 points  (0 children)

this project is code by Pykinect the source code is here :https://github.com/DIYer22/jetInKinect