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kshitijthakkar/loggenix-moe-0.4b-cactus
loggenix-moe-0.4b-cactus is a machine learning model from kshitijthakkar. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for cactus. The card lists the license as apache-2.0.
Pre-converted weights for Loggenix/loggenix-moe-0.4b-0.2a-sft-s3.1 in Cactus format for on-device inference.
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Updated Feb 23, 2026
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From the Hugging Face model README
Pre-converted weights for Loggenix/loggenix-moe-0.4b-0.2a-sft-s3.1 in Cactus format for on-device inference.
| Property | Value |
|---|---|
| Architecture | Qwen3MoeForCausalLM |
| Parameters | ~0.4B (active ~0.2B per token) |
| Experts | 16 experts, top-2 routing |
| Hidden Dim | 512 |
| Layers | 12 |
| Attention Heads | 8 (2 KV heads) |
| Expert FFN Dim | 768 |
| Context Length | 262,144 tokens |
| Precision | FP16 |
| Vocab Size | 151,936 |
These weights are in Cactus binary format (.weights files + config.txt), converted from HuggingFace safetensors using the Cactus Python conversion pipeline.
This is not a standard HuggingFace Transformers model. It is designed to be loaded directly by the Cactus C++ inference engine for mobile and edge deployment (iOS, Android, macOS, Linux ARM64).
Download the entire repo and point Cactus to the directory:
# Clone weights
git clone https://huggingface.co/kshitijthakkar/loggenix-moe-0.4b-cactus
# Use with Cactus engine
cactus run ./loggenix-moe-0.4b-cactus
Converted using the Cactus Python converter from the original safetensors:
cactus convert Loggenix/loggenix-moe-0.4b-0.2a-sft-s3.1 ./output --precision FP16
See the original model card for license details.