Pre-quantized GGUF binaries for
Aether 2.3
, scaling up to the powerful
Qwen2.5-3B-Instruct
base architecture.
Trained with SFT (Supervised Fine-Tuning) and PEFT (LoRA) on a custom 3 GB dataset using local NVIDIA RTX GPU acceleration, Aether 2.3 delivers high intelligence, robust conversational capabilities, and exceptional multilingual performance in German and English.
🔗
Looking for the Base / LoRA Adapter?
If you want to use the Hugging Face Transformers PEFT adapter instead, check out the main repository:
👉
Maxilicious20/Aether-2.3
📦 Available Files & Quantizations
Choose the right file depending on your system's VRAM/RAM and performance needs:
Filename
Quantization
Quality
Size
Description / Recommendation
aether_2_3_fp16.gguf
FP16 / F16
Maximum
~5.75 GB
Uncompressed full precision. Best quality, requires more VRAM.
aether_2_3_q8_0.gguf
Q8_0
Very High
~3.05 GB
Near-lossless quantization. Excellent balance of precision and speed.
aether_2_3_q4_k_m.gguf
Q4_K_M
Balanced
~1.79 GB
Recommended.
Best compromise between speed, size, and minimal quality loss.
🚀 How to Run Locally
1. LM Studio
Open LM Studio.
Search for
Maxilicious20/Aether-2.3-GGUF
or paste the repo ID.
Download your preferred quantization (e.g.,
aether_2_3_q4_k_m.gguf
).
Load the model and start chatting!
2. Ollama / llama.cpp
You can run the GGUF file directly using
llama.cpp
:
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Maxilicious20 Aether-2.3-GGUF online free url in huggingface.co:
Aether-2.3-GGUF is an open source model from GitHub that offers a free installation service, and any user can find Aether-2.3-GGUF on GitHub to install. At the same time, huggingface.co provides the effect of Aether-2.3-GGUF install, users can directly use Aether-2.3-GGUF installed effect in huggingface.co for debugging and trial. It also supports api for free installation.