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 4858[Quote]

/lmg/ - a general dedicated to the discussion and development of local language models.

SoyGenesis Edition

Previous Threads: Too Cucked 4 mentioning.

►News
>(04/16) Microsoft releases Bitnet B1.58 https://hf.co/microsoft/bitnet-b1.58-2B-4T
>(04/14) GLM-4-0414 and GLM-Z1 released: https://hf.co/collections/THUDM/glm-4-0414-67f3cbcb34dd9d252707cb2e
>(04/14) Nemotron-H hybrid models released: https://hf.co/collections/nvidia/nemotron-h-67fd3d7ca332cdf1eb5a24bb
>(04/10) Ultra long context Llama-3.1-8B: https://hf.co/collections/nvidia/ultralong-67c773cfe53a9a518841fbbe

►News Archive: https://rentry.org/lmg-news-archive
►Glossary: https://rentry.org/lmg-glossary
►Links: https://rentry.org/LocalModelsLinks
►Official /lmg/ card: https://files.catbox.moe/cbclyf.png

►Getting Started
https://rentry.org/lmg-lazy-getting-started-guide
https://rentry.org/lmg-build-guides
https://rentry.org/IsolatedLinuxWebService
https://rentry.org/tldrhowtoquant

►Further Learning
https://rentry.org/machine-learning-roadmap
https://rentry.org/llm-training
https://rentry.org/LocalModelsPapers

►Benchmarks
LiveBench: https://livebench.ai
Programming: https://livecodebench.github.io/leaderboard.html
Code Editing: https://aider.chat/docs/leaderboards
Context Length: https://github.com/hsiehjackson/RULER
Japanese: https://hf.co/datasets/lmg-anon/vntl-leaderboard
Censorbench: https://codeberg.org/jts2323/censorbench
GPUs: https://github.com/XiongjieDai/GPU-Benchmarks-on-LLM-Inference

►Tools
Alpha Calculator: https://desmos.com/calculator/ffngla98yc
GGUF VRAM Calculator: https://hf.co/spaces/NyxKrage/LLM-Model-VRAM-Calculator
Sampler Visualizer: https://artefact2.github.io/llm-sampling

►Text Gen. UI, Inference Engines
https://github.com/lmg-anon/mikupad
https://github.com/oobabooga/text-generation-webui
https://github.com/LostRuins/koboldcpp
https://github.com/ggerganov/llama.cpp
https://github.com/theroyallab/tabbyAPI
https://github.com/vllm-project/vllm

 10869[Quote]

>>10620
commits were being made as early as march that in the past indicated a launch being <2 weeks away. The current narrative is that its taking so long because they're releasing a large number of different model sizes.

Honestly I'd rather see a gigantic QwQ.

 11094[Quote]

I loaded glm and a few other most recent models trying to continue the ERP with fetish of my choice. Rerolled 10-20 times for each model. Each time I was fucking disgusted with the output. Most LLM's were basically saying the same thing, but rewording it slightly Then I loaded a hentai game that isn't the fetish of my choice but slightly adjacent, made LLM translate it and I came buckets. This hobby is so fucking depressing. And the censorship is the work of a devil. I refuse to believe current models would be unable to generalize fucking ERP. They get intentionally gimped to be worthless, while still spitting out some disgusting simulacra of what smut should be that will condition you to stop thinking of AI as an alternative to biological whores. I FUCKING HATE THIS CLOWN WORLD

 11255[Quote]

Support for multimodal input + output model Janus has been merged into transformers
https://github.com/huggingface/transformers/releases/tag/v4.51.3-Janus-preview

 11310[Quote]

>>10762
Thanks.

 11326[Quote]

The latest Deepseek v3 has ruined me for any other model.

 11332[Quote]

I've been using LLMs since December 2022. I am increasingly concerned that LLMs are not AI, but just glorified calculators.

 11406[Quote]

>>11332
>I've been using LLMs since December 2022. I am increasingly concerned that LLMs are not AI, but just glorified calculators.

Calculators dont really talk to me or give me useful suggestions for console commands/ API calls

>>11326
Idk man, I have been using R1 because its an allrounder, is V3 really that much better? Dont want another massive model on my drive. Not like inference would be much faster (okay, there are no think tags for V3)

 11413[Quote]

>>11406
>Calculators dont really talk to me or give me useful suggestions for console commands/ API calls
That's why I said glorified calculators.

 11416[Quote]

>>11413
Guess you could argue that they are (probabilistic if seed is chosen at random) linear bounded turing machines.
One of main issues remain their incapability to learn in realm time. At best, an LLM has in context learning



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