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
@@ -22599,3 +22599,39 @@
     - filename: Almost-Human-X3-32bit-1839-6B.i1-Q4_K_M.gguf
       sha256: 5dc9766b505d98d7a5ad960b321c1fafe508734ca12ff4b7c480f8afbbc1e03b
       uri: huggingface://mradermacher/Almost-Human-X3-32bit-1839-6B-i1-GGUF/Almost-Human-X3-32bit-1839-6B.i1-Q4_K_M.gguf
+- !!merge <<: *llama3
+  name: "home-1b-v3"
+  urls:
+    - https://huggingface.co/acon96/Home-1B-v3-GGUF
+  description: |
+    **Model Name:** TinyLlama-1.1B-Chat-v1.0
+    **Base Model:** TinyLlama-1.1B (a 1.1-billion-parameter Llama-based model pretrained on 3 trillion tokens)
+    **Fine-Tuned For:** Conversational AI with a focus on instruction following and function calling
+    **Training Approach:**
+    - First fine-tuned on synthetic dialogue data (variant of UltraChat)
+    - Further refined using DPO (Direct Preference Optimization) on the UltraFeedback dataset (64k human-AI preference pairs ranked by GPT-4)
+    - Follows the Zephyr prompt format for chat interactions
+
+    **Key Features:**
+    - Lightweight and efficient, ideal for edge devices and low-resource environments
+    - Capable of generating natural, engaging responses with a pirate-style persona (or adaptable tone)
+    - Designed for seamless integration with chat interfaces using Hugging Face’s tokenizer chat templates
+    - Supports structured output for function calling (e.g., integrating with Home Assistant)
+
+    **Use Cases:**
+    - Conversational agents, chatbots, personal assistants
+    - Local/edge deployment (e.g., Raspberry Pi)
+    - Custom AI assistants requiring small footprint and high efficiency
+
+    **License:** Apache 2.0 (compatible with the original Llama 2 license)
+
+    **Repository:** [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0)
+
+    > ✅ **Note:** The model described here is the **original, unquantized base model**. The repository `acon96/Home-1B-v3-GGUF` contains a **quantized version** of a fine-tuned variant of this model (Home 1B v3), which is optimized for low-resource Home Assistant deployments.
+  overrides:
+    parameters:
+      model: Home-1B-v3.q4_k_m.gguf
+  files:
+    - filename: Home-1B-v3.q4_k_m.gguf
+      sha256: d8635ef0ae6d3465dfd7badca711281e2a947f15c6998ec4d222517bfb35b693
+      uri: huggingface://acon96/Home-1B-v3-GGUF/Home-1B-v3.q4_k_m.gguf