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
@@ -23049,3 +23049,22 @@
     - filename: YanoljaNEXT-Rosetta-27B-2511.i1-Q4_K_M.gguf
       sha256: 0a599099e93ad521045e17d82365a73c1738fff0603d6cb2c9557e96fbc907cb
       uri: huggingface://mradermacher/YanoljaNEXT-Rosetta-27B-2511-i1-GGUF/YanoljaNEXT-Rosetta-27B-2511.i1-Q4_K_M.gguf
+- !!merge <<: *qwen25coder
+  name: "gigsama-tool-call-v2"
+  urls:
+    - https://huggingface.co/skaffum/gigsama-tool-call-v2-gguf
+  description: |
+    The model **gigsama-tool-call-v2-gguf** is a quantized version of a larger language model fine-tuned for tool calling capabilities, specifically designed to interact with external tools in a structured and reliable manner. It is based on a foundational LLM architecture (likely a variant of Llama or similar) and has been further optimized for tasks involving API calls, function execution, and reasoning in tool-augmented workflows.
+
+    The "gguf" suffix indicates that this is a quantized model format (developed by the GGUF project), which allows for efficient inference on consumer hardware such as CPUs and lower-end GPUs. The original model was likely trained or fine-tuned by the **GigSama** team (or community contributors) to improve performance in tool-use scenarios, such as dynamic data retrieval, code execution, or API integration.
+
+    Important note: This is **not** the original model authored by the foundational model provider. It is a downstream, quantized variant created for accessibility and performance, and therefore lacks the original author’s full technical documentation. For the base, unquantized model and original training details, you should refer to the original repository or model card from the base architecture (e.g., Llama 3, Mistral, etc.) used in the training pipeline.
+
+    This model is ideal for developers and researchers seeking lightweight, efficient tool-use inference with minimal hardware requirements.
+  overrides:
+    parameters:
+      model: Merged-Model-1.7B-Q4_K_M.gguf
+  files:
+    - filename: Merged-Model-1.7B-Q4_K_M.gguf
+      sha256: bdd7c1d93bd7fa5fb8524a5c386aa6c828e4a62a9ac0e6159b56b4cf5a044629
+      uri: huggingface://skaffum/gigsama-tool-call-v2-gguf/Merged-Model-1.7B-Q4_K_M.gguf