POCKET-Image Studio
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Perfect text in any language, in any image
Alex Hant
hardhant
AI & ML interests
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liked a Space 3 days ago
FINAL-Bench/POCKET-Image-Studio liked a model 3 days ago
FINAL-Bench/POCKET-Image-Zimage liked a model 5 days ago
microsoft/Mage-Flow-Edit-TurboOrganizations
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reacted to OppaAI's post with 👍 6 days ago
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3175
Try to chat with my AI Waifu in Japanese
Now that I have setup my AI Waifu running 24/7 in my Jetson Orin Nano (running at 25W top), I can talk to her anytime anywhere I want, on cellphone, tablet, or PC, as long as there is internet access.
Tonight I gave it a try to speak with my AI Waifu, with my not so great Japanese, just to test if ASR can pick up my Nihongo and the TTS can speak out Waifu's Japanese dialogue properly.
Turns out she is just as verbose and as heavily leaked with materials from system prompt as in English. Only this time I cannot fully understand.
I need to find some way to turn her into my Japanese tutor...
GitHub 🔗: https://github.com/OppaAI/Aiko-chan/
Now that I have setup my AI Waifu running 24/7 in my Jetson Orin Nano (running at 25W top), I can talk to her anytime anywhere I want, on cellphone, tablet, or PC, as long as there is internet access.
Tonight I gave it a try to speak with my AI Waifu, with my not so great Japanese, just to test if ASR can pick up my Nihongo and the TTS can speak out Waifu's Japanese dialogue properly.
Turns out she is just as verbose and as heavily leaked with materials from system prompt as in English. Only this time I cannot fully understand.
I need to find some way to turn her into my Japanese tutor...
GitHub 🔗: https://github.com/OppaAI/Aiko-chan/
- 5 replies
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reacted to danielhanchen's post with 🚀 9 days ago
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5617
Gemma 4 is now faster and much more accurate! 🚀
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4
- 8 replies
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reacted to satgeze's post with 🤗 21 days ago
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3614
First GGUF quants of Tencent's Hy3 (299B MoE), built before official llama.cpp support exists.
Hy3 dropped ~30 hours ago with only MLX and MXFP4 quants, both datacenter-sized. So I converted it myself using a community llama.cpp fork that implements the hy_v3 architecture.
What's in the repo:
- IQ1_M (62GB, fits a 128GB MacBook), IQ2_M (90GB), Q2_K (101GB), all with 1M context baked in via YaRN
- IQ quants are importance-matrix: bootstrap style. The static Q2_K ran RAM-resident to compute the imatrix, then IQ1_M and IQ2_M were requantized from the archived f16 with it
- Fixed chat template (the stock one uses .format() calls llama.cpp's Jinja rejects)
- Build instructions for the fork, including the two gotchas that cost me three build attempts
Honesty section, because that is how these repos work: this is EXPERIMENTAL. Not needle-certified yet (1M is baked but unverified, certification ladder will be published either way). MTP layer exists in the checkpoint but no llama.cpp build can run hy_v3 MTP inference yet, so it is not included. Real gate outputs are on the card, misses and all, judge for yourself.
satgeze/Hy3-1M-GGUF
Full quant ladder (Q3 through Q8) is mirroring to ModelScope for bigger hardware.
Hy3 dropped ~30 hours ago with only MLX and MXFP4 quants, both datacenter-sized. So I converted it myself using a community llama.cpp fork that implements the hy_v3 architecture.
What's in the repo:
- IQ1_M (62GB, fits a 128GB MacBook), IQ2_M (90GB), Q2_K (101GB), all with 1M context baked in via YaRN
- IQ quants are importance-matrix: bootstrap style. The static Q2_K ran RAM-resident to compute the imatrix, then IQ1_M and IQ2_M were requantized from the archived f16 with it
- Fixed chat template (the stock one uses .format() calls llama.cpp's Jinja rejects)
- Build instructions for the fork, including the two gotchas that cost me three build attempts
Honesty section, because that is how these repos work: this is EXPERIMENTAL. Not needle-certified yet (1M is baked but unverified, certification ladder will be published either way). MTP layer exists in the checkpoint but no llama.cpp build can run hy_v3 MTP inference yet, so it is not included. Real gate outputs are on the card, misses and all, judge for yourself.
satgeze/Hy3-1M-GGUF
Full quant ladder (Q3 through Q8) is mirroring to ModelScope for bigger hardware.
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model 21 days ago
reacted to danielhanchen's post with 🔥 21 days ago
Post
6103
DeepSeek-V4 can now run locally with Unsloth GGUFs! 🐳
Run lossless DeepSeek-V4-Flash on 168GB RAM or
3-bit works on 110GB Mac, RAM, VRAM setups.
Run via Unsloth Studio or llama.cpp.
GGUF: unsloth/DeepSeek-V4-Flash-GGUF
Guide: https://unsloth.ai/docs/models/deepseek-v4
Run lossless DeepSeek-V4-Flash on 168GB RAM or
3-bit works on 110GB Mac, RAM, VRAM setups.
Run via Unsloth Studio or llama.cpp.
GGUF: unsloth/DeepSeek-V4-Flash-GGUF
Guide: https://unsloth.ai/docs/models/deepseek-v4
liked a
model 22 days ago
