chore(model gallery): 🤖 add 1 new models via gallery agent

gallery/index.yaml

@@ -3295,7 +3295,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -3313,7 +3313,7 @@
   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:
@@ -3331,7 +3331,7 @@
   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:
@@ -6949,7 +6949,7 @@
       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
@@ -23075,3 +23075,77 @@
     - filename: Orca-Agent-v0.1.Q4_K_M.gguf
       sha256: 2943397fe2c23959215218adbfaf361ca7974bbb0f948e08c230e6bccb1f130a
       uri: huggingface://mradermacher/Orca-Agent-v0.1-GGUF/Orca-Agent-v0.1.Q4_K_M.gguf
+- !!merge <<: *qwen3
+  name: "orca-agent-v0.1-i1"
+  urls:
+    - https://huggingface.co/mradermacher/Orca-Agent-v0.1-i1-GGUF
+  description: |
+    **Model Name:** Orca-Agent-v0.1
+    **Base Model:** Qwen3-14B
+    **Repository:** [Danau5tin/Orca-Agent-v0.1](https://huggingface.co/Danau5tin/Orca-Agent-v0.1)
+    **License:** Apache 2.0
+    **Use Case:** Multi-Agent Orchestration for Complex Code & System Tasks
+
+    ---
+
+    ### 🔍 **Overview**
+    Orca-Agent-v0.1 is a powerful **task orchestration agent** designed to manage complex, multi-step workflows—especially in code and system administration—without directly modifying code. Instead, it acts as a strategic planner that coordinates a team of specialized agents.
+
+    ---
+
+    ### 🛠️ **Key Features**
+    - **Intelligent Task Breakdown:** Analyzes user requests and decomposes them into focused subtasks.
+    - **Agent Coordination:** Dynamically dispatches:
+      - *Explorer agents* to understand the system state.
+      - *Coder agents* to implement changes with precise instructions.
+      - *Verifier agents* to validate results.
+    - **Context Management:** Maintains a persistent context store to track discoveries across steps.
+    - **High Performance:** Achieves **18.25% on TerminalBench** when paired with Qwen3-Coder-30B, nearing the performance of a 480B model.
+
+    ---
+
+    ### 📊 **Performance**
+    | Orchestrator | Subagent | Terminal Bench |
+    |--------------|----------|----------------|
+    | Orca-Agent-v0.1-14B | Qwen3-Coder-30B | **18.25%** |
+    | Qwen3-14B | Qwen3-Coder-30B | 7.0% |
+
+    > *Trained on 32x H100s using GRPO + curriculum learning, with full open-source training code available.*
+
+    ---
+
+    ### 📌 **Example Output**
+    ```xml
+    <task_create>
+    agent_type: 'coder'
+    title: 'Attempt recovery using the identified backup file'
+    description: |
+      Move the backup file from /tmp/terraform_work/.terraform.tfstate.tmp to /infrastructure/recovered_state.json.
+      Verify file existence, size, and permissions (rw-r--r--).
+    max_turns: 10
+    context_refs: ['task_003']
+    </task_create>
+    ```
+
+    ---
+
+    ### 📁 **Serving**
+    - ✅ **vLLM:** `vllm serve Danau5tin/Orca-Agent-v0.1`
+    - ✅ **SGLang:** `python -m sglang.launch_server --model-path Danau5tin/Orca-Agent-v0.1`
+
+    ---
+
+    ### 🌐 **Learn More**
+    - **Training & Code:** [GitHub - Orca-Agent-RL](https://github.com/Danau5tin/Orca-Agent-RL)
+    - **Orchestration Framework:** [multi-agent-coding-system](https://github.com/Danau5tin/multi-agent-coding-system)
+
+    ---
+
+    > ✅ *Note: The model at `mradermacher/Orca-Agent-v0.1-i1-GGUF` is a quantized version of this original model. This description reflects the full, unquantized version by the original author.*
+  overrides:
+    parameters:
+      model: Orca-Agent-v0.1.i1-Q4_K_M.gguf
+  files:
+    - filename: Orca-Agent-v0.1.i1-Q4_K_M.gguf
+      sha256: 05548385128da98431f812d1b6bc3f1bff007a56a312dc98d9111b5fb51e1751
+      uri: huggingface://mradermacher/Orca-Agent-v0.1-i1-GGUF/Orca-Agent-v0.1.i1-Q4_K_M.gguf