chore(model gallery): 🤖 add new models via gallery agent (#6536)

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
This commit is contained in:
LocalAI [bot]
2025-10-18 13:48:19 +02:00
committed by GitHub
parent 7f88abb3b1
commit 354bf5debb

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@@ -22139,3 +22139,33 @@
- filename: Qwen-SEA-LION-v4-32B-IT.i1-Q4_K_M.gguf
sha256: 66dd1e818186d5d85cadbabc8f6cb105545730caf4fe2592501bec93578a6ade
uri: huggingface://mradermacher/Qwen-SEA-LION-v4-32B-IT-i1-GGUF/Qwen-SEA-LION-v4-32B-IT.i1-Q4_K_M.gguf
- !!merge <<: *qwen3
name: "zirel-2-i1"
urls:
- https://huggingface.co/mradermacher/Zirel-2-i1-GGUF
description: |
**Model Name:** Zirel-2
**Base Model:** Qwen/Qwen3-30B-A3B-Instruct-2507 (Mixture-of-Experts)
**Author:** Daemontatox
**License:** Apache 2.0
**Description:**
Zirel-2 is a highly capable, efficiency-optimized fine-tuned language model based on Qwen's 30B MoE architecture. It leverages only ~3.3B active parameters per inference step, delivering dense-model performance while minimizing resource usage. Designed for high reasoning, code generation, and long-context tasks (up to 262K tokens), it excels as a smart, responsive assistant. Ideal for deployment on consumer hardware or resource-constrained environments.
**Key Features:**
- Mixture-of-Experts (MoE) design for efficiency
- 30.5B total parameters, 3.3B active per inference
- Long context (262,144 tokens)
- Optimized for reasoning, instruction-following, and creative generation
- Available in GGUF format for local inference
**Use Case:** Personal AI assistant, code & content generation, complex reasoning tasks.
*Note: The GGUF version in `mradermacher/Zirel-2-i1-GGUF` is a quantized derivative; the original model is `Daemontatox/Zirel-2`.*
overrides:
parameters:
model: Zirel-2.i1-Q4_K_S.gguf
files:
- filename: Zirel-2.i1-Q4_K_S.gguf
sha256: 9856e987f5f59c874a8fe26ffb2a2c5b7c60b85186131048536b3f1d91a235a6
uri: huggingface://mradermacher/Zirel-2-i1-GGUF/Zirel-2.i1-Q4_K_S.gguf