LocalLLaMA

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Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.

Get support from the community! Ask questions, share prompts, discuss benchmarks, get hyped at the latest and greatest model releases! Enjoy talking about our awesome hobby.

As ambassadors of the self-hosting machine learning community, we strive to support each other and share our enthusiasm in a positive constructive way.

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Rule 1 - No harassment or personal character attacks of community members. I.E no namecalling, no generalizing entire groups of people that make up our community, no baseless personal insults.

Rule 2 - No comparing artificial intelligence/machine learning models to cryptocurrency. I.E no comparing the usefulness of models to that of NFTs, no comparing the resource usage required to train a model is anything close to maintaining a blockchain/ mining for crypto, no implying its just a fad/bubble that will leave people with nothing of value when it burst.

Rule 3 - No comparing artificial intelligence/machine learning to simple text prediction algorithms. I.E statements such as "llms are basically just simple text predictions like what your phone keyboard autocorrect uses, and they're still using the same algorithms since <over 10 years ago>.

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founded 2 years ago

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pax@sh.itjust.works

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Smokeydope@lemmy.world

MonsterBug@sh.itjust.works

Am I the only one who is really impressed by Granite4 from IBM? (lemmy.zip)

submitted 2 weeks ago* (last edited 2 weeks ago) by possiblylinux127@lemmy.zip to c/localllama@sh.itjust.works

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It is small but still really good

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[–] Smokeydope@lemmy.world 5 points 2 weeks ago* (last edited 2 weeks ago) (1 children)

Havent heard of it till this post, what about it impressed you over something like llama, mistral, qwen?

for anyone who wants more info its a 7b Mixture of Experts model released under apache 2.0!

" Granite-4-Tiny-Preview is a 7B parameter fine-grained hybrid mixture-of-experts (MoE) instruct model fine-tuned from Granite-4.0-Tiny-Base-Preview using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets tailored for solving long context problems. This model is developed using a diverse set of techniques with a structured chat format, including supervised fine-tuning, and model alignment using reinforcement learning."

Supported Languages: English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. However, users may fine-tune this Granite model for languages beyond these 12 languages.

Intended Use: This model is designed to handle general instruction-following tasks and can be integrated into AI assistants across various domains, including business applications.

Capabilities

Thinking
Summarization
Text classification
Text extraction
Question-answering
Retrieval Augmented Generation (RAG)
Code related tasks
Function-calling tasks
Multilingual dialog use cases
Long-context tasks including long document/meeting summarization, long document QA, etc.

https://huggingface.co/ibm-granite/granite-4.0-tiny-preview

[–] Xylight@lemdro.id 3 points 2 weeks ago* (last edited 2 weeks ago) (1 children)

there's also a "small" and "micro" variant, which are 32b a6b MoE and 3b dense models respectively

[–] basxto@discuss.tchncs.de 1 points 2 weeks ago (1 children)

granite4:micro-h should be able to run on machines with 4GB RAM

[–] Xylight@lemdro.id 2 points 2 weeks ago

You can run Qwen3 4b thinking at q4 quantization at 2.5GB, which is probably a better model too