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
@@ -23109,3 +23109,44 @@
     - filename: Qwen3-Nemotron-32B-RLBFF.i1-Q4_K_M.gguf
       sha256: 000e8c65299fc232d1a832f1cae831ceaa16425eccfb7d01702d73e8bd3eafee
       uri: huggingface://mradermacher/Qwen3-Nemotron-32B-RLBFF-i1-GGUF/Qwen3-Nemotron-32B-RLBFF.i1-Q4_K_M.gguf
+- !!merge <<: *gptoss
+  name: "financial-gpt-oss-20b-q8-i1"
+  urls:
+    - https://huggingface.co/mradermacher/financial-gpt-oss-20b-q8-i1-GGUF
+  description: |
+    ### **Financial GPT-OSS 20B (Base Model)**
+
+    **Model Type:** Causal Language Model (Fine-tuned for Financial Analysis)
+    **Architecture:** Mixture of Experts (MoE) – 20B parameters, 32 experts (4 active per token)
+    **Base Model:** `unsloth/gpt-oss-20b-unsloth-bnb-4bit`
+    **Fine-tuned With:** LoRA (Low-Rank Adaptation) on financial conversation data
+    **Training Data:** 22,250 financial dialogue pairs covering stocks (AAPL, NVDA, TSLA, etc.), technical analysis, risk assessment, and trading signals
+    **Context Length:** 131,072 tokens
+    **Quantization:** Q8_0 GGUF (for efficient inference)
+    **License:** Apache 2.0
+
+    **Key Features:**
+    - Specialized in financial market analysis: technical indicators (RSI, MACD), risk assessments, trading signals, and price forecasts
+    - Handles complex financial queries with structured, actionable insights
+    - Designed for real-time use with low-latency inference (GGUF format)
+    - Supports S&P 500 stocks and major asset classes across tech, healthcare, energy, and finance sectors
+
+    **Use Case:** Ideal for traders, analysts, and developers building financial AI tools. Use with caution—**not financial advice**.
+
+    **Citation:**
+    ```bibtex
+    @misc{financial-gpt-oss-20b-q8,
+      title={Financial GPT-OSS 20B Q8: Fine-tuned Financial Analysis Model},
+      author={beenyb},
+      year={2025},
+      publisher={Hugging Face Hub},
+      url={https://huggingface.co/beenyb/financial-gpt-oss-20b-q8}
+    }
+    ```
+  overrides:
+    parameters:
+      model: financial-gpt-oss-20b-q8.i1-Q4_K_M.gguf
+  files:
+    - filename: financial-gpt-oss-20b-q8.i1-Q4_K_M.gguf
+      sha256: 14586673de2a769f88bd51f88464b9b1f73d3ad986fa878b2e0c1473f1c1fc59
+      uri: huggingface://mradermacher/financial-gpt-oss-20b-q8-i1-GGUF/financial-gpt-oss-20b-q8.i1-Q4_K_M.gguf