Qwen
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Error on loading I-Quality model
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#1 opened 3 days ago
by Emerald7664
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Novel APEX Quant of Moonshot 16B model
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#1 opened 21 days ago
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Myric
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reacted to appvoid's post with 🔥 12 days ago
Post
1410
A Small Model is All You Need. Meet
After 3 years of experiments, we are finally releasing our flagship tiny model: **palmer-006**.
If you are building for edge hardware, SBCs (Raspberry Pi, etc.), or low-power devices, this is for you. Inspired by Andrej Karpathy's idea of a self-contained "cognitive core," we wanted to see how much power we could pack into a sub-100M parameter footprint.
🧠 **How we "Palmerized" it:**
We believe in starting our experiments with the absolute strongest baseline possible.
1. Light fine-tuning on highly curated data
2. Model merging
3. Another light fine-tuning round
4. Adjusted Mamba for maximum token speed ⚡️
⚠️ *Note: This is a foundational language model. It has not been instruction-tuned yet!*
Also, since this needs instruction tuning next to become a chat assistant—**what dataset would you recommend we use for the instruct tune?**
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🔗 **Quick Links & Info:**
* **License:** Open for research, education, hobby, and modification! (For commercial use/hosted APIs, shoot an email to nosoyhackercodigo@gmail.com. *PS: Donators can claim a free commercial license!*)
* **Attribution:** Built using AI tech from the Technology Innovation Institute (TII).
Can't wait to see what you build at the edge. Let me know your prompt completions below! 👇
appvoid/palmer-006
palmer-006 (90M)After 3 years of experiments, we are finally releasing our flagship tiny model: **palmer-006**.
If you are building for edge hardware, SBCs (Raspberry Pi, etc.), or low-power devices, this is for you. Inspired by Andrej Karpathy's idea of a self-contained "cognitive core," we wanted to see how much power we could pack into a sub-100M parameter footprint.
🧠 **How we "Palmerized" it:**
We believe in starting our experiments with the absolute strongest baseline possible.
1. Light fine-tuning on highly curated data
2. Model merging
3. Another light fine-tuning round
4. Adjusted Mamba for maximum token speed ⚡️
⚠️ *Note: This is a foundational language model. It has not been instruction-tuned yet!*
Also, since this needs instruction tuning next to become a chat assistant—**what dataset would you recommend we use for the instruct tune?**
---
🔗 **Quick Links & Info:**
* **License:** Open for research, education, hobby, and modification! (For commercial use/hosted APIs, shoot an email to nosoyhackercodigo@gmail.com. *PS: Donators can claim a free commercial license!*)
* **Attribution:** Built using AI tech from the Technology Innovation Institute (TII).
Can't wait to see what you build at the edge. Let me know your prompt completions below! 👇
appvoid/palmer-006
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model 13 days ago
reacted to Nymbo's post with 🔥 15 days ago
Post
5586
Introducing Inflect-v2, two exceptionally small, open-weight English TTS models at just 3.9M and 9.3M parameters. Both generate speech multiple times faster than real-time on CPU. Despite their size, Inflect-v2 delivers quality that is competitive with much larger lightweight TTS systems, including KittenTTS, Piper, and Supertonic-3.
CPU, CUDA, PyTorch, and ONNX are supported. Apache 2.0.
See it for yourselves:
owensong/Inflect-Micro-v2
owensong/Inflect-Nano-v2
Try the Demos:
Nymbo/Inflect-TTS (unlimited CPU usage)
owensong/Inflect-v2 (ultra-fast ZeroGPU usage)
CPU, CUDA, PyTorch, and ONNX are supported. Apache 2.0.
See it for yourselves:
owensong/Inflect-Micro-v2
owensong/Inflect-Nano-v2
Try the Demos:
Nymbo/Inflect-TTS (unlimited CPU usage)
owensong/Inflect-v2 (ultra-fast ZeroGPU usage)
- 6 replies
Accelerator.GPU works or not?
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#1 opened 22 days ago
by 
Emerald7664
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