Deploying DeepSeek on 96 H100 GPUs (lmsys.org)

Screenshot of lmsys.org: Deploying DeepSeek on 96 H100 GPUs

First screen, captured 1 year ago.

Looks similar

Screenshot of lmsys.org: DeepSeek-V4 on Day 0: From Fast Inference to Verified RL with SGLang and Miles

DeepSeek-V4 on Day 0: From Fast Inference to Verified RL with SGLang and Miles (lmsys.org)

50 points by mji 6 months ago | 5 comments

Screenshot of skeptrune.com: LLM codegen go brrr – Parallelization with Git worktrees and tmux

LLM codegen go brrr – Parallelization with Git worktrees and tmux (skeptrune.com)

144 points by skeptrune 1 year ago | 66 comments

Screenshot of lmsys.org: How long can open-source LLMs truly promise on context length?

How long can open-source LLMs truly promise on context length?(lmsys.org)

174 points by dacheng2 3 years ago | 58 comments

Screenshot of efraingaray.com: TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14

TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14 (efraingaray.com)

21 points by EfrainGaray 28 days ago | 9 comments

Blog post benchmarking TabPFN and TabICL foundation models against tuned XGBoost on fourteen tabular datasets, finding the no-training models won all fourteen.

tabpfn tabicl xgboost tabular-data

Screenshot of pretty-radio-b75.notion.site: DeepScaleR: Surpassing O1-Preview with a 1.5B Model by Scaling RL

DeepScaleR: Surpassing O1-Preview with a 1.5B Model by Scaling RL (pretty-radio-b75.notion.site)

279 points by sijuntan 1 year ago | 111 comments

Screenshot of andlukyane.com: Testing MiniMax M2.7 via API on three real ML and coding workflows

Testing MiniMax M2.7 via API on three real ML and coding workflows (andlukyane.com)

26 points by Artgor 5 months ago | 2 comments

Looks similar

DeepSeek-V4 on Day 0: From Fast Inference to Verified RL with SGLang and Miles(lmsys.org)

LLM codegen go brrr – Parallelization with Git worktrees and tmux(skeptrune.com)

How long can open-source LLMs truly promise on context length?(lmsys.org)

TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14(efraingaray.com)

DeepScaleR: Surpassing O1-Preview with a 1.5B Model by Scaling RL(pretty-radio-b75.notion.site)

Testing MiniMax M2.7 via API on three real ML and coding workflows(andlukyane.com)

DeepSeek-V4 on Day 0: From Fast Inference to Verified RL with SGLang and Miles (lmsys.org)

LLM codegen go brrr – Parallelization with Git worktrees and tmux (skeptrune.com)

TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14 (efraingaray.com)

DeepScaleR: Surpassing O1-Preview with a 1.5B Model by Scaling RL (pretty-radio-b75.notion.site)

Testing MiniMax M2.7 via API on three real ML and coding workflows (andlukyane.com)