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

gallery/index.yaml

@@ -3127,7 +3127,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -3145,7 +3145,7 @@
   description: |
     google/gemma-3-12b-it is an open-source, state-of-the-art, lightweight, multimodal model built from the same research and technology used to create the Gemini models. It is capable of handling text and image input and generating text output. It has a large context window of 128K tokens and supports over 140 languages. The 12B variant has been fine-tuned using the instruction-tuning approach. Gemma 3 models are suitable for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes them deployable in environments with limited resources such as laptops, desktops, or your own cloud infrastructure.
   overrides:
     #mmproj: gemma-3-12b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-12b-it-Q4_K_M.gguf
   files:
@@ -3163,7 +3163,7 @@
   description: |
     Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. Gemma 3 models are multimodal, handling text and image input and generating text output, with open weights for both pre-trained variants and instruction-tuned variants. Gemma 3 has a large, 128K context window, multilingual support in over 140 languages, and is available in more sizes than previous versions. Gemma 3 models are well-suited for a variety of text generation and image understanding tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as laptops, desktops or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone. Gemma-3-4b-it is a 4 billion parameter model.
   overrides:
     #mmproj: gemma-3-4b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-4b-it-Q4_K_M.gguf
   files:
@@ -6781,7 +6781,7 @@
       sha256: 2756551de7d8ff7093c2c5eec1cd00f1868bc128433af53f5a8d434091d4eb5a
       uri: huggingface://Triangle104/Nano_Imp_1B-Q8_0-GGUF/nano_imp_1b-q8_0.gguf
 - &qwen25
   name: "qwen2.5-14b-instruct" ## Qwen2.5
   icon: https://avatars.githubusercontent.com/u/141221163
   url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
   license: apache-2.0
@@ -22079,3 +22079,39 @@
     - filename: Tlacuilo-12B.i1-Q4_K_M.gguf
       sha256: 94218112aa02113c8e21cd2c1d10818bea39bc6aee7e67be6014f86e80e76cb1
       uri: huggingface://mradermacher/Tlacuilo-12B-i1-GGUF/Tlacuilo-12B.i1-Q4_K_M.gguf
+- !!merge <<: *qwen3
+  name: "qwen-sea-lion-v4-32b-it-i1"
+  urls:
+    - https://huggingface.co/mradermacher/Qwen-SEA-LION-v4-32B-IT-i1-GGUF
+  description: |
+    **Model Name:** Qwen-SEA-LION-v4-32B-IT
+    **Base Model:** Qwen3-32B
+    **Model Type:** Instruction-tuned Large Language Model (LLM)
+    **Languages:** English, Chinese, Burmese, Indonesian, Malay, Filipino, Tamil, Thai, Vietnamese, Khmer, Lao, and more (11+ SEA and global languages)
+    **Context Length:** 128,000 tokens
+    **License:** Qwen Terms of Service / Qwen Usage Policy
+    **Developer:** Products Pillar, AI Singapore (funded by Singapore NRF)
+
+    **Description:**
+    Qwen-SEA-LION-v4-32B-IT is a large, multilingual, instruction-tuned language model specifically designed for the Southeast Asia (SEA) region. Built on the Qwen3-32B foundation, it underwent continued pre-training on 100B tokens from the SEA-Pile v2 corpus and fine-tuned on 8 million high-quality question-answer pairs to enhance instruction-following and multi-turn dialogue performance.
+
+    This model excels in understanding and generating content across 11+ Southeast Asian and global languages, making it ideal for regional applications in education, customer service, content creation, and research. With a context length of 128k tokens, it supports long-form reasoning, summarization, and document analysis.
+
+    > **Note:** Not safety-aligned—users should perform additional fine-tuning for safety-critical applications.
+
+    **Use Case Highlights:**
+    ✅ Multilingual support for SEA languages
+    ✅ Strong instruction-following and chat capabilities
+    ✅ High-capacity context for complex reasoning
+    ✅ Optimized for real-world regional deployment
+
+    **Access:**
+    Available on Hugging Face: [aisingapore/Qwen-SEA-LION-v4-32B-IT](https://huggingface.co/aisingapore/Qwen-SEA-LION-v4-32B-IT)
+    For commercial use or inquiries, contact: [sealion@aisingapore.org](mailto:sealion@aisingapore.org)
+  overrides:
+    parameters:
+      model: Qwen-SEA-LION-v4-32B-IT.i1-Q4_K_M.gguf
+  files:
+    - 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