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
@@ -23149,3 +23149,57 @@
     - 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
+- !!merge <<: *qwen3
+  name: "spiral-qwen3-4b-multi-env"
+  urls:
+    - https://huggingface.co/mradermacher/Spiral-Qwen3-4B-Multi-Env-GGUF
+  description: |
+    **Model Name:** Spiral-Qwen3-4B-Multi-Env
+    **Base Model:** Qwen3-4B (fine-tuned variant)
+    **Repository:** [spiral-rl/Spiral-Qwen3-4B-Multi-Env](https://huggingface.co/spiral-rl/Spiral-Qwen3-4B-Multi-Env)
+    **Quantized Version:** Available via GGUF (by mradermacher)
+
+    ---
+
+    ### 📌 Description:
+
+    Spiral-Qwen3-4B-Multi-Env is a fine-tuned, instruction-optimized version of the Qwen3-4B language model, specifically enhanced for multi-environment reasoning and complex task execution. Built upon the foundational Qwen3-4B architecture, this model demonstrates strong performance in coding, logical reasoning, and domain-specific problem-solving across diverse environments.
+
+    The model was developed by **spiral-rl**, with contributions from the community, and is designed to support advanced, real-world applications requiring robust reasoning, adaptability, and structured output generation. It is optimized for use in constrained environments, making it ideal for edge deployment and low-latency inference.
+
+    ---
+
+    ### 🔧 Key Features:
+    - **Architecture:** Qwen3-4B (Decoder-only, Transformer-based)
+    - **Fine-tuned For:** Multi-environment reasoning, instruction following, and complex task automation
+    - **Language Support:** English (primary), with strong multilingual capability
+    - **Model Size:** 4 billion parameters
+    - **Training Data:** Proprietary and public datasets focused on reasoning, coding, and task planning
+    - **Use Case:** Ideal for agent-based systems, automated workflows, and intelligent decision-making in dynamic environments
+
+    ---
+
+    ### 📦 Availability:
+    While the original base model is hosted at `spiral-rl/Spiral-Qwen3-4B-Multi-Env`, a **quantized GGUF version** is available for efficient inference on consumer hardware:
+    - **Repository:** [mradermacher/Spiral-Qwen3-4B-Multi-Env-GGUF](https://huggingface.co/mradermacher/Spiral-Qwen3-4B-Multi-Env-GGUF)
+    - **Quantizations:** Q2_K to Q8_0 (including IQ4_XS), f16, and Q4_K_M recommended for balance of speed and quality
+
+    ---
+
+    ### 💡 Ideal For:
+    - Local AI agents
+    - Edge deployment
+    - Code generation and debugging
+    - Multi-step task planning
+    - Research in low-resource reasoning systems
+
+    ---
+
+    > ✅ **Note:** The model card above reflects the *original, unquantized base model*. The quantized version (GGUF) is optimized for performance but may have minor quality trade-offs. For full fidelity, use the base model with full precision.
+  overrides:
+    parameters:
+      model: Spiral-Qwen3-4B-Multi-Env.Q4_K_M.gguf
+  files:
+    - filename: Spiral-Qwen3-4B-Multi-Env.Q4_K_M.gguf
+      sha256: e91914c18cb91f2a3ef96d8e62a18b595dd6c24fad901dea639e714bc7443b09
+      uri: huggingface://mradermacher/Spiral-Qwen3-4B-Multi-Env-GGUF/Spiral-Qwen3-4B-Multi-Env.Q4_K_M.gguf