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Fine-tuning Mistral 7B with LoRA on a 32 GB M1 (laptop!) in MLX Updated example uses less RAM + support for custom datasets 🚀

Awni Hannun

44,866 subscribers

148,153 просмотров • 2 лет назад •via X (Twitter)

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Комментарии: 10

Фото профиля murat 🍥

murat 🍥2 лет назад

i was just about to ask if anyone's done LoRA/QLoRA on mlx yet. exciting!

Фото профиля Delip Rao e/σ

Delip Rao e/σ2 лет назад

can you talk to the gods that are and make MLX work on my M2 w/ 14.2 (23C63)?

Фото профиля Awni Hannun

Awni Hannun2 лет назад

😬 It should run no prob for you! Send me your issue, we'll definitely debug

Фото профиля Eric Hartford

Eric Hartford2 лет назад

@winglian you think axolotl could work on mlx?

Фото профиля Peter J. Liu

Peter J. Liu2 лет назад

Some performance comparisons with GPUs, e.g. 4090 would be useful.

Фото профиля Rahul Dave

Rahul Dave2 лет назад

Guessing this needs 32! Darn it I got a 16…

Фото профиля Jay

Jay2 лет назад

Can’t wait to couple this with @textcortex desktop app 🔩

Фото профиля ae

ae2 лет назад

any chance that it runs on 8G M2 macbook?

Фото профиля thyself Know

thyself Know2 лет назад

I only have 16 GB RAM 😭

Фото профиля John Gorman

John Gorman2 лет назад

@awnihannun @abacaj Yup - I'm be priming my Mixtral Q6 on my 32GB M1 to check out MLX ;)

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42,413 просмотров • 3 месяцев назад

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108,746 просмотров • 4 месяцев назад

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h100envy

13,856 просмотров • 19 дней назад

Stop paying for every API call. Download once and run forever. My 1-post “thread” on Gemma. → Gemma is Google’s open weights model family. → Gemma runs locally on laptop and phone. → Gemma 3N is optimized for low RAM devices. → Variants exist for medical and safety and embeddings. → Fine tuning lets you build custom models for your niche. Save this video, you’ll build your first local AI tool. Want the SOP? DM me. 💬

Stop paying for every API call. Download once and run forever. My 1-post “thread” on Gemma. → Gemma is Google’s open weights model family. → Gemma runs locally on laptop and phone. → Gemma 3N is optimized for low RAM devices. → Variants exist for medical and safety and embeddings. → Fine tuning lets you build custom models for your niche. Save this video, you’ll build your first local AI tool. Want the SOP? DM me. 💬

Julian Goldie SEO

14,403 просмотров • 7 месяцев назад

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MolmoAct2 runs zero-shot on an SO-ARM101, no training required 🦾 Ai2 open Action Reasoning Model is now in LeRobot with the full lifecycle covered: fine-tuning (full or LoRA), evaluation, and real-robot deployment. It pairs a Molmo2-ER vision-language backbone with a flow-matching action expert to turn images, language, and proprioceptive state into action chunks. The best part: ready-made checkpoints ship with calibration correction baked in, so you can point it at your SO-100/101 and just watch it work. Inference fits in ~12GB at bf16, and LoRA fine-tuning runs on a single 24GB GPU. Big thanks to the Ai2 team for building this in the open.

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20,066 просмотров • 24 дней назад