chore(model gallery): 🤖 add 1 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
@@ -22542,3 +22542,35 @@
     - filename: gpt-oss-20b-Esper3.1.i1-Q4_K_M.gguf
       sha256: 079683445913d12e70449a10b9e1bfc8adaf1e7917e86cf3be3cb29cca186f11
       uri: huggingface://mradermacher/gpt-oss-20b-Esper3.1-i1-GGUF/gpt-oss-20b-Esper3.1.i1-Q4_K_M.gguf
+- !!merge <<: *llama4
+  name: "inclusionai.ring-1t"
+  urls:
+    - https://huggingface.co/DevQuasar/inclusionAI.Ring-1T-GGUF
+  description: |
+    **Model Name:** Ring-1T
+    **Repository:** [inclusionAI/Ring-1T](https://huggingface.co/inclusionAI/Ring-1T)
+    **License:** MIT
+    **Pipeline:** Text Generation
+    **Architecture:** Ling 2.0 (MoE-based), 1 trillion total parameters (50B activated)
+    **Context Length:** Up to 128K tokens (supports YaRN scaling)
+    **Training:** Large-scale verifiable reward reinforcement learning (RLVR), optimized with Icepop stabilization and ASystem framework
+
+    **Overview:**
+    Ring-1T is a trillion-parameter open-source foundation model designed for deep reasoning and advanced natural language understanding. Built upon the Ling-1T-base, it excels in complex tasks including math competitions (AIME, IMO), code generation (LiveCodeBench, ICPC), logical reasoning (ARC-AGI), and creative writing. Trained using innovative reinforcement learning techniques like Icepop and ASystem, Ring-1T achieves state-of-the-art performance among open-source models while maintaining stability during long-sequence generation.
+
+    **Key Features:**
+    - High performance across reasoning, coding, and creative tasks
+    - Support for 128K context with YaRN extension
+    - Openly available for research, fine-tuning, and deployment via Hugging Face and ModelScope
+    - Compatible with SGLang, vLLM, and Llama-Factory for efficient inference and customization
+
+    **Ideal For:** Researchers, developers, and AI practitioners seeking a powerful, open alternative for advanced reasoning and long-context applications.
+
+    👉 Try online: [ZenMux](https://zenmux.ai/inclusionai/ring-1t) | 📥 Download: [Hugging Face](https://huggingface.co/inclusionAI/Ring-1T) | [ModelScope](https://www.modelscope.cn/models/inclusionAI/Ring-1T)
+  overrides:
+    parameters:
+      model: inclusionAI.Ring-1T.Q4_K_M-00001-of-00047.gguf
+  files:
+    - filename: inclusionAI.Ring-1T.Q4_K_M-00001-of-00047.gguf
+      sha256: 769611061e2780688ba92ff2003ff0e93135fd0f01542aeec8fbd9e888135b2e
+      uri: huggingface://DevQuasar/inclusionAI.Ring-1T-GGUF/inclusionAI.Ring-1T.Q4_K_M-00001-of-00047.gguf