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Leonie

@helloiamleonie • 20,732 subscribers

Post-training @liquidai

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日本語でも問題ない😌

日本語でも問題ない😌

46,262 views

this local model has less than 3.14B params

this local model has less than 3.14B params

65,193 views

reachy mini assembly timelapse (~2 hrs)

reachy mini assembly timelapse (~2 hrs)

52,517 views

I vibe coded a visual PDF search app with ColQwen2. This is how it works: - Store PDF files as images in a Weaviate AI Database vector database - Embed images and text with a multimodal late-interaction model (ColQwen2) - Generate token-wise (and summed) similarity maps to highlight image patches with high similarity Now I need to refactor the messy vibe-coded project. In the meantime, you can check out the Notebook this demo is based on to try it out yourself:

I vibe coded a visual PDF search app with ColQwen2. This is how it works: - Store PDF files as images in a Weaviate AI Database vector database - Embed images and text with a multimodal late-interaction model (ColQwen2) - Generate token-wise (and summed) similarity maps to highlight image patches with high similarity Now I need to refactor the messy vibe-coded project. In the meantime, you can check out the Notebook this demo is based on to try it out yourself:

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LFM2.5-2.6B is live! At only 2.6B, it shouldn't be this good at agentic tasks. Here you can see how a 100% local agent is cleaning up my Desktop. I wrote a step-by-step guide on how to set it up yourself: • Model: LFM2.5-2.6B • Server of choice: llama.cpp, LMStudio, and more • Harness of choice: OpenClaw, Hermes Agent, Pi
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LFM2.5-2.6B is live! At only 2.6B, it shouldn't be this good at agentic tasks. Here you can see how a 100% local agent is cleaning up my Desktop. I wrote a step-by-step guide on how to set it up yourself: • Model: LFM2.5-2.6B • Server of choice: llama.cpp, LMStudio, and more • Harness of choice: OpenClaw, Hermes Agent, Pi

Leonie

63,641 views • 1 month ago

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