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We’re open-sourcing PorTAL, our framework for shared task representations and cross model LoRA adaptation. It now spans from hybrid attention models to multimodal systems including Gemma 4 E2B, Mistral 7B & Thinking Machines' Inkling. Code: ramp-public/portallib Models: Hugging Face /RampPublic

171,845 views • 2 months ago •via X (Twitter)

24 Comments

Ramp Labs's profile picture
Ramp Labs2 months ago

Code: Models + data: PyPI:

Ramp's profile picture
Ramp2 months ago

@thinkymachines OPEN IT UP

Ben Geist's profile picture
Ben Geist2 months ago

@thinkymachines OSS is short for ossome

Ryan Amiri's profile picture
Ryan Amiri2 months ago

@thinkymachines @miramurati you seeing what I'm seeing?

shevchenko's profile picture
shevchenko2 months ago

@thinkymachines You're telling me a portal trained this Lora?

Alex L's profile picture
Alex L2 months ago

@thinkymachines Ramp Labs ♥️ OSS

Terry Chen's profile picture
Terry Chen2 months ago

@thinkymachines Is this still the credit card company? 😟

AI Mastery Guide's profile picture
AI Mastery Guide2 months ago

@thinkymachines Cross model adaptation, open sourced for everyone.

Jalen Xing's profile picture
Jalen Xing2 months ago

@thinkymachines lfg

sandra's profile picture
sandra2 months ago

@thinkymachines based based based

Marena's profile picture
Marena2 months ago

@thinkymachines Shared representations could simplify model adaptation

Shubhayan Srivastava's profile picture
Shubhayan Srivastava2 months ago

@thinkymachines Ahh yes the AI lab for finance

Nick Venturi's profile picture
Nick Venturi2 months ago

@thinkymachines running this tonight instead of sleeping

ghostkey.base.eth's profile picture
ghostkey.base.eth2 months ago

@thinkymachines Open source everything.

René Sultan's profile picture
René Sultan2 months ago

@thinkymachines @b_geist did you a try a LoRA for you posts?

Steven Cheng's profile picture
Steven Cheng2 months ago

@thinkymachines Cross-model LoRA adaptation is a huge unlock. Really curious to see how the shared task representations handle the gap between hybrid attention and multimodal systems like Gemma.

Rain Li's profile picture
Rain Li2 months ago

@thinkymachines huge

Jurly's profile picture
Jurly2 months ago

@thinkymachines This is huge for the open-source ecosystem 🔥

Sebastian Buzdugan's profile picture
Sebastian Buzdugan2 months ago

@thinkymachines cross-model lora usually breaks on tokenizer drift before attention differences show up

安叫兽|Bird🕊️ 🔶 BNB's profile picture
安叫兽|Bird🕊️ 🔶 BNB2 months ago

@thinkymachines 跨模型 LoRA 这块终于有人系统搞了

Yechan Do's profile picture
Yechan Do2 months ago

@thinkymachines Did they pivot to AI company?

buildwithjay's profile picture
buildwithjay2 months ago

@thinkymachines PorTAL is interesting because Ramp has production pain behind it. infra launches land better when the use case is not imaginary

Elon Orbit's profile picture
Elon Orbit2 months ago

@thinkymachines If PorTAL unifies adapters across model families, my fine-tuning costs collapse. Big if true. Any vision-language benchmarks yet?

Ah Oh's profile picture
Ah Oh2 months ago

@thinkymachines Freezing the task representation and core decoder and recalibrating only the aligner is a clean split. What I'd want to know is how far the aligner stretches before it breaks - Mistral 7B to a multimodal base like Gemma 4 E2B is a big jump in representation geometry.

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