Estwld/GENOME-gemma-2b-it
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Nature-Inspired Population-Based Evolution of Large Language Models
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TheDrummer/Skyfall-36B-v2
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Exciting releases from the Chinese community this February🔥
👉 zh-ai-community/2025-february-67a35aaa68e97812def5b6ef
MLLM:
✨ Ovis2 by Alibaba
AIDC-AI/ovis2-67ab36c7e497429034874464
✨ Step Audio Chat by StepFun AI
stepfun-ai/step-audio-67b33accf45735bb21131b0b
Audio:
✨ Step Audio TTS by StepFunAI
stepfun-ai/Step-Audio-TTS-3B
✨ InspireMusic by Alibaba
https://huggingface.co/FunAudioLLM
✨ Baichuan Audio by BaichuanAI
baichuan-inc/Baichuan-Audio-Instruct
Video:
✨ Wan2.1 by Alibaba_Wan
Wan-AI/Wan2.1-T2V-14B
✨ Stepvideo-T2V by StepFun AI
stepfun-ai/stepvideo-t2v
✨ SkyReels-V1 by Skywork
Skywork/skyreels-v1-67b34676ff65b4ec02d16307
✨ LLaDA-8B by RenminUniversity
GSAI-ML/LLaDA-8B-Instruct
MoE:
✨ Moonlight-16B by MoonshotAI (Kimi)
moonshotai/Moonlight-16B-A3B-Instruct
Reasoning:
✨ TinyR1-32B by Qihoo360
qihoo360/TinyR1-32B-Preview
Dataset:
✨ Chinese DeepSeek R1-Distill data -110k
Congliu/Chinese-DeepSeek-R1-Distill-data-110k
👉 zh-ai-community/2025-february-67a35aaa68e97812def5b6ef
MLLM:
✨ Ovis2 by Alibaba
AIDC-AI/ovis2-67ab36c7e497429034874464
✨ Step Audio Chat by StepFun AI
stepfun-ai/step-audio-67b33accf45735bb21131b0b
Audio:
✨ Step Audio TTS by StepFunAI
stepfun-ai/Step-Audio-TTS-3B
✨ InspireMusic by Alibaba
https://huggingface.co/FunAudioLLM
✨ Baichuan Audio by BaichuanAI
baichuan-inc/Baichuan-Audio-Instruct
Video:
✨ Wan2.1 by Alibaba_Wan
Wan-AI/Wan2.1-T2V-14B
✨ Stepvideo-T2V by StepFun AI
stepfun-ai/stepvideo-t2v
✨ SkyReels-V1 by Skywork
Skywork/skyreels-v1-67b34676ff65b4ec02d16307
✨ LLaDA-8B by RenminUniversity
GSAI-ML/LLaDA-8B-Instruct
MoE:
✨ Moonlight-16B by MoonshotAI (Kimi)
moonshotai/Moonlight-16B-A3B-Instruct
Reasoning:
✨ TinyR1-32B by Qihoo360
qihoo360/TinyR1-32B-Preview
Dataset:
✨ Chinese DeepSeek R1-Distill data -110k
Congliu/Chinese-DeepSeek-R1-Distill-data-110k
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FluxSpace: Disentangled Semantic Editing in Rectified Flow Transformers
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2412.09611
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Published
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10
1.58-bit FLUX
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2412.18653
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80
Deep Neuromorphic Networks with Superconducting Single Flux Quanta
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2311.10721
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2
FLUX that Plays Music
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2409.00587
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33
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Debugging Tags:
Imagine, Associated Thoughts, Dialectical Analysis, Backwards Induction, Metacognition, and Normal Thought Processes such as <think> or <begin_of_thought>
Edit: Uploaded new images w/ a Open WebUI function to organize the tags.
Open WebUI Function: https://openwebui.com/f/quaz93/imagine_phi
This Phi-4 model is part of a test project that I called Micro-Dose. My goal was to use a small dataset to activate reasoning and other cognitive processes without relying on a large dataset.
I found that this was possible with a tiny dataset of just 90 rows, specifically designed as math problems. In the initial iterations, the dataset only activated reasoning when a math-related question was asked. I then made a few changes to the dataset’s structure, including the order of information and the naming of tags. You can see the sample results in the pictures. Not really anything special, just thought I'd share.
Tweaked the dataset a bit:
Quazim0t0/Imagine-Phi-v0.2-GGUF
Quazim0t0/MicroDoseV0.2
First image shows the new tags, second shows the regular thought process and the third is the model in combination with web searches
Imagine, Associated Thoughts, Dialectical Analysis, Backwards Induction, Metacognition, and Normal Thought Processes such as <think> or <begin_of_thought>
Edit: Uploaded new images w/ a Open WebUI function to organize the tags.
Open WebUI Function: https://openwebui.com/f/quaz93/imagine_phi
This Phi-4 model is part of a test project that I called Micro-Dose. My goal was to use a small dataset to activate reasoning and other cognitive processes without relying on a large dataset.
I found that this was possible with a tiny dataset of just 90 rows, specifically designed as math problems. In the initial iterations, the dataset only activated reasoning when a math-related question was asked. I then made a few changes to the dataset’s structure, including the order of information and the naming of tags. You can see the sample results in the pictures. Not really anything special, just thought I'd share.
Tweaked the dataset a bit:
Quazim0t0/Imagine-Phi-v0.2-GGUF
Quazim0t0/MicroDoseV0.2
First image shows the new tags, second shows the regular thought process and the third is the model in combination with web searches
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Making Browser-Based Inference Actually Usable
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