Qwen/Qwen3.6-35B-A3B
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Peter Stewart
poita66
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cyankiwi/Qwen3.6-35B-A3B-AWQ-4bit:Small safetensor file liked a model about 12 hours ago
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Small safetensor file
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#1 opened about 12 hours ago
by 
tasticleeze
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Hugging Face Changelog
Agent Traces on the Hub
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Latest Revision Won't Load on 2x3090
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#6 opened 19 days ago
by poita66
Tried looking at it on mobile, the sticky filter section takes most of the vertical viewport space, so you can’t really see the results
reacted to branikita's post with ❤️ about 1 month ago
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We tested our 3D-printed parallel gripper for the SO-ARM100/101 robotic platform, successfully handling a 1.5 kg payload. The gripper features a 100.5mm full stroke and ±0.05mm repeatability — all for around $76 in parts and 30 minutes of assembly.
Full source code, STL files, and assembly guide are open-source and available on GitHub: https://github.com/roboninecom/SO-ARM100-101-Parallel-Gripper
Full source code, STL files, and assembly guide are open-source and available on GitHub: https://github.com/roboninecom/SO-ARM100-101-Parallel-Gripper
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reacted to marksverdhei's post with 🤯 about 2 months ago
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# The most underrated feature of Qwen3-TTS: Voice embeddings! 🧑🦰💬
https://huggingface.co/collections/marksverdhei/qwen3-voice-embedding
Did you know that Qwen3 TTS actually utilizes voice embedding?
Your voice is turned into a vector of 1024 (or 2048) dimensions,
and based on this vector alone you can get your custom voice.
But the coolest part is that this means that you can use math to modify voices, average voices. You can swap gender, pitch, mix and match vocies, and even create an emotion space! This also enables semantic voice search!
The voice embedding model is actually just a tiny encoder with just a few million parameters. I've ripped it out of the voice embeding model so you can use the embedding model standalone. Check out my collection! :D
https://huggingface.co/collections/marksverdhei/qwen3-voice-embedding
Did you know that Qwen3 TTS actually utilizes voice embedding?
Your voice is turned into a vector of 1024 (or 2048) dimensions,
and based on this vector alone you can get your custom voice.
But the coolest part is that this means that you can use math to modify voices, average voices. You can swap gender, pitch, mix and match vocies, and even create an emotion space! This also enables semantic voice search!
The voice embedding model is actually just a tiny encoder with just a few million parameters. I've ripped it out of the voice embeding model so you can use the embedding model standalone. Check out my collection! :D
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