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

gallery/index.yaml

@@ -1,4 +1,47 @@
 ---
+- name: "deepseek-v3.2-speciale"
+  url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
+  urls:
+    - https://huggingface.co/ubergarm/DeepSeek-V3.2-Speciale-GGUF
+  description: |
+    **Model Description:**
+    The `deepseek-ai/DeepSeek-V3.2-Speciale` model is a large language model optimized for deep reasoning tasks. This quantized version (available as `ubergarm/DeepSeek-V3.2-Speciale-GGUF`) is a compressed, efficient deployment of the base model, designed for accelerated inference on hardware like GPUs or CPUs. It uses **ik_llama.cpp** for quantization, offering memory-efficient variants with varying bit-precision (e.g., Q8_0, IQ5_K, IQ3_K, IQ2_KS, IQ1_KT) to balance performance and accuracy.
+
+    **Key Features:**
+      - **Base Model:** `deepseek-ai/DeepSeek-V3.2-Speciale` (optimized for reasoning).
+      - **Quantization:** Compressed with `ik_llama.cpp` for reduced memory footprint (e.g., 179GB for `smol-IQ2_KS`).
+      - **Use Cases:** Ideal for tasks requiring deep contextual understanding, such as code generation, translation, and complex reasoning.
+      - **Hardware Support:** Compatible with CUDA 12.9+ and Windows builds for CUDA 12.8.
+
+    **License:** MIT.
+
+    **Available Quantizations:**
+      - `Q8_0` (664GB): High accuracy, 8.504 BPW.
+      - `IQ5_K` (464GB): 5.946 BPW, optimized for performance.
+      - `IQ3_K` (290GB): 3.724 BPW, further reduced memory.
+      - `smol-IQ2_KS` (179GB): 2.297 BPW, smallest variant.
+      - `smol-IQ1_KT` (146GB): 1.871 BPW, even smaller for resource-constrained use.
+
+    **Note:** This quantized model is not the original author's version and is tailored for efficient inference with tools like `ik_llama.cpp`. It is designed for deep reasoning tasks and requires GPU/CPU hardware support.
+  overrides:
+    parameters:
+      model: llama-cpp/models/DeepSeek-V3.2-Speciale-smol-IQ2_KS-00005-of-00005.gguf
+    name: DeepSeek-V3.2-Speciale-GGUF
+    backend: llama-cpp
+    template:
+      use_tokenizer_template: true
+    known_usecases:
+      - chat
+    function:
+      grammar:
+        disable: true
+    description: Imported from https://huggingface.co/ubergarm/DeepSeek-V3.2-Speciale-GGUF
+    options:
+      - use_jinja:true
+  files:
+    - filename: llama-cpp/models/DeepSeek-V3.2-Speciale-smol-IQ2_KS-00005-of-00005.gguf
+      sha256: 2bce0f5490fd97c73a0f9b2d49952065ed31d4ff22a9d75efef1e6c1fa9656e6
+      uri: https://huggingface.co/ubergarm/DeepSeek-V3.2-Speciale-GGUF/resolve/main/smol-IQ2_KS/DeepSeek-V3.2-Speciale-smol-IQ2_KS-00005-of-00005.gguf
 - name: "liquidai.lfm2-2.6b-transcript"
   url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
   urls:
@@ -3722,7 +3765,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -3740,7 +3783,7 @@
   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:
@@ -3758,7 +3801,7 @@
   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:
@@ -6976,7 +7019,7 @@
       sha256: 2756551de7d8ff7093c2c5eec1cd00f1868bc128433af53f5a8d434091d4eb5a
       uri: huggingface://Triangle104/Nano_Imp_1B-Q8_0-GGUF/nano_imp_1b-q8_0.gguf
 - &smollm
   url: "github:mudler/LocalAI/gallery/chatml.yaml@master" ## SmolLM
   name: "smollm-1.7b-instruct"
   icon: https://huggingface.co/datasets/HuggingFaceTB/images/resolve/main/banner_smol.png
   tags:
@@ -7020,7 +7063,7 @@
       sha256: decd2598bc2c8ed08c19adc3c8fdd461ee19ed5708679d1c54ef54a5a30d4f33
       uri: huggingface://HuggingFaceTB/SmolLM2-1.7B-Instruct-GGUF/smollm2-1.7b-instruct-q4_k_m.gguf
 - &llama31
   url: "github:mudler/LocalAI/gallery/llama3.1-instruct.yaml@master" ## LLama3.1
   icon: https://avatars.githubusercontent.com/u/153379578
   name: "meta-llama-3.1-8b-instruct"
   license: llama3.1