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Maxilicious20/Aether-2.2-GGUF overview

Aether 2.2 GGUF Pre quantized GGUF binaries for Aether 2.2 . Trained with SFT Supervised Fine Tuning and PEFT LoRA on a custom dataset using local NVIDIA RTX Gโ€ฆ

ggufllama.cpplm-studioaethergermanenglishtext-generationdeenlicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~940.4 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

3 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
aether_2_2_f16.ggufGGUFF162.88 GBDownload
aether_2_2_q4_k_m.ggufGGUFQ4_K_M940.4 MBDownload
aether_2_2_q8_0.ggufGGUFQ8_01.53 GBDownload

Model Details

Model IDMaxilicious20/Aether-2.2-GGUF
AuthorMaxilicious20
Pipelinetext-generation
Licenseapache-2.0
Base modelโ€”
Last modified2026-08-01T10:20:11.000Z

Model README

---

library_name: gguf

tags:

  • gguf
  • llama.cpp
  • lm-studio
  • aether
  • german
  • english
  • text-generation

license: apache-2.0

language:

  • de
  • en

---

Aether 2.2 - GGUF

Pre-quantized GGUF binaries for Aether 2.2.

Trained with SFT (Supervised Fine-Tuning) and PEFT (LoRA) on a custom dataset using local NVIDIA RTX GPU acceleration, Aether 2.2 provides fast, light-weight, and accurate conversational text generation in German and English.

> ๐Ÿ”— Looking for the Base / LoRA Adapter?

> If you want to use the Hugging Face Transformers PEFT adapter instead, check out the main repository:

> ๐Ÿ‘‰ Maxilicious20/Aether-2.2

---

๐Ÿ“ฆ 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_2_f16.gguf | FP16 / F16 | Maximum | ~2.88 GB | Uncompressed full precision. Best quality. |

| aether_2_2_q8_0.gguf | Q8_0 | Very High | ~1.53 GB | Near-lossless quantization. Excellent balance of precision and speed. |

| aether_2_2_q4_k_m.gguf | Q4_K_M | Balanced | ~940 MB | Recommended. Best compromise between speed, size, and minimal quality loss. |

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๐Ÿš€ How to Run Locally

1. LM Studio

  1. Open LM Studio.
  2. Search for Maxilicious20/Aether-2.2-GGUF or paste the repository ID.
  3. Download your preferred quantization (e.g., aether_2_2_q4_k_m.gguf).
  4. Load the model and start chatting!

2. Ollama / llama.cpp

You can run the GGUF file directly using llama.cpp:

./llama-cli -m aether_2_2_q4_k_m.gguf -p "Hello Aether!" -n 256

Run Maxilicious20/Aether-2.2-GGUF with guIDE

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