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liked 4 models about 1 month ago

coreml-community/coreml-CounterfeitXL-V2.0

Text-to-Image • Updated Apr 10, 2024 • 7

cagliostrolab/animagine-xl-3.1

Text-to-Image • 3B • Updated Dec 22, 2025 • 231k • 728

AngelSlim/Hy3-GGUF

Text Generation • 295B • Updated Jul 21 • 384k • 184

mateogrgic/GLM-5.2-colibri-int4-with-int8-mtp

Updated Jul 14 • 3.26k • 138

liked 2 models about 2 months ago

InternScience/Agents-A1

Text Generation • 35B • Updated Jul 15 • 12.2k • 633

empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF

Image-Text-to-Text • 9B • Updated Jul 14 • 436k • 2.62k

liked a model 2 months ago

bosonai/higgs-tts-3-4b

Text-to-Speech • 5B • Updated Jul 9 • 237k • 722

liked a model 3 months ago

ideogram-ai/ideogram-4-fp8

Text-to-Image • 9B • Updated Jun 3 • 39.9k • • 754

upvoted a collection 4 months ago

Gemma 4

Collection

88 items • Updated Jun 3 • 147

liked 5 models 4 months ago

deepseek-ai/DeepSeek-V4-Flash

Text Generation • 291B • Updated Jun 22 • 1.79M • • 2.13k

iffrce/OmniCoder-9B-GGUF

9B • Updated Apr 2 • 132 • 1

Tesslate/OmniCoder-9B

Text Generation • 9B • Updated Mar 13 • 1.17k • 676

inferencerlabs/Qwen3.6-35B-A3B-MLX-Q9

Image-Text-to-Text • 11B • Updated May 24 • 511 • 5

Dogacel/DeepSeek-OCR-Metal-MPS

Image-Text-to-Text • 3B • Updated Dec 24, 2025 • 30 • 13

liked 4 models 10 months ago

dx8152/Qwen-Image-Edit-2509-Relight

Image-to-Image • Updated Nov 12, 2025 • 7.51k • • 225

vandijklab/C2S-Scale-Gemma-2-27B

Text Generation • 28B • Updated Oct 31, 2025 • 2.07k • 174

McGill-NLP/delethink-96k-1.5b

2B • Updated Oct 9, 2025 • 8 • 3

vngrs-ai/Kumru-2B

Text Generation • 2B • Updated Sep 26, 2025 • 1.16k • 120

New activity in LiquidAI/LFM2-1.2B 10 months ago

the chat template might be incorrect: missing `<|tool_call_start|>` part in chat_template.jinja

7

#17 opened 11 months ago by

kumapo

reacted to Severian's post with 🔥 11 months ago

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Post

3272

MLX port of BDH (Baby Dragon Hatchling) is up!

I’ve ported the BDH ( https://github.com/pathwaycom/bdh ) model to MLX for Apple Silicon. It’s a faithful conversion of the PyTorch version: same math, same architecture (byte-level vocab, shared weights across layers, ReLU sparsity, RoPE attention with Q=K), with MLX-friendly APIs and a detailed README explaining the few API-level differences and why results are equivalent.

Code, docs, and training script are ready to use. You may need to adjust the training script a bit to fit your own custom dataset. Only tested on M4 so far, but should work perfect for any M1/M2/M3 users out there.

I’m currently training this MLX build on my Internal Knowledge Map (IKM) dataset Severian/Internal-Knowledge-Map
Training’s underway; expect a day or so before I publish weights. When it’s done, I’ll upload the checkpoint to Hugging Face for anyone to test.

Repo: https://github.com/severian42/BDH-MLX
HF model (coming soon): Severian/BDH-MLX

If you try it on your own data, feedback and PRs are welcome.

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