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
@@ -22100,3 +22100,42 @@
     - filename: PositiveDetox-Qwen2.5-14B.Q4_K_S.gguf
       sha256: abd224325aea504a61fb749cc12649641165c33035b4e5923163387370878005
       uri: huggingface://mradermacher/PositiveDetox-Qwen2.5-14B-GGUF/PositiveDetox-Qwen2.5-14B.Q4_K_S.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
+    **Type:** Instruction-tuned Large Language Model (LLM)
+    **Language Support:** 11 languages including English, Mandarin, Burmese, Indonesian, Malay, Filipino, Tamil, Thai, Vietnamese, Khmer, and Lao
+    **Context Length:** 128,000 tokens
+    **Repository:** [aisingapore/Qwen-SEA-LION-v4-32B-IT](https://huggingface.co/aisingapore/Qwen-SEA-LION-v4-32B-IT)
+    **License:** [Qwen Terms of Service](https://qwen.ai/termsservice) / [Qwen Usage Policy](https://qwen.ai/usagepolicy)
+
+    **Overview:**
+    Qwen-SEA-LION-v4-32B-IT is a high-performance, multilingual instruction-tuned LLM developed by AI Singapore, specifically optimized for Southeast Asia (SEA). Built on the Qwen3-32B foundation, it underwent continued pre-training on 100B tokens from the SEA-Pile v2 corpus and further fine-tuned on ~8 million question-answer pairs to enhance instruction-following and reasoning. Designed for real-world multilingual applications across government, education, and business sectors in Southeast Asia, it delivers strong performance in dialogue, content generation, and cross-lingual tasks.
+
+    **Key Features:**
+    - Trained for 11 major SEA languages with high linguistic accuracy
+    - 128K token context for long-form content and complex reasoning
+    - Optimized for instruction following, multi-turn dialogue, and cultural relevance
+    - Available in full precision and quantized variants (4-bit/8-bit)
+    - Not safety-aligned — suitable for downstream safety fine-tuning
+
+    **Use Cases:**
+    - Multilingual chatbots and virtual assistants in SEA regions
+    - Cross-lingual content generation and translation
+    - Educational tools and public sector applications in Southeast Asia
+    - Research and development in low-resource language modeling
+
+    **Note:** This model is not safety-aligned. Use with caution and consider additional alignment measures for production deployment.
+
+    **Contact:** [sealion@aisingapore.org](mailto:sealion@aisingapore.org) for inquiries.
+  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