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Cydonia-24B-v4.3-AWQ – AI Model by tacodevs | AlphaNeural AI

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tacodevs/
Cydonia-24B-v4.3-AWQ

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creative-writing

text-generation

TheDrummer/Cydonia-24B-v4.3

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Cydonia-24B-v4.3-AWQ

AWQ 4-bit quantization of TheDrummer/Cydonia-24B-v4.3.

Quantization Details

Method: AWQ (Activation-aware Weight Quantization)
Bits: 4-bit
Group size: 128
Version: GEMM
Zero point: True
Model size: ~14 GB (vs ~48 GB FP16)

Usage

Works with vLLM, Transformers, and other AWQ-compatible inference engines.

bash

# vLLM
vllm serve Irvollo/Cydonia-24B-v4.3-AWQ --quantization awq_marlin --dtype float16

# Transformers
from awq import AutoAWQForCausalLM
model = AutoAWQForCausalLM.from_quantized("Irvollo/Cydonia-24B-v4.3-AWQ")

Original Model

Cydonia v4.3 by TheDrummer — a Mistral Small 3.1 24B fine-tune optimized for roleplay and creative writing.

Hardware Requirements

Minimum: 16 GB VRAM (RTX 4090, A100, etc.)
Recommended: 24 GB VRAM for comfortable KV cache headroom