chore(model gallery): add nvidia_nemotron-research-reasoning-qwen-1.5b

gallery/index.yaml

@@ -988,7 +988,7 @@
     - gemma3
     - gemma-3
   overrides:
     #mmproj: gemma-3-27b-it-mmproj-f16.gguf
     parameters:
       model: gemma-3-27b-it-Q4_K_M.gguf
   files:
@@ -1006,7 +1006,7 @@
   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:
@@ -1024,7 +1024,7 @@
   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:
@@ -4057,7 +4057,7 @@
       sha256: b9f01bead9e163db9351af036d8d63ef479d7d48a1bb44934ead732a180f371c
       uri: huggingface://bartowski/Menlo_ReZero-v0.1-llama-3.2-3b-it-grpo-250404-GGUF/Menlo_ReZero-v0.1-llama-3.2-3b-it-grpo-250404-Q4_K_M.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
@@ -6018,7 +6018,7 @@
       sha256: 0fec82625f74a9a340837de7af287b1d9042e5aeb70cda2621426db99958b0af
       uri: huggingface://bartowski/Chuluun-Qwen2.5-72B-v0.08-GGUF/Chuluun-Qwen2.5-72B-v0.08-Q4_K_M.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:
@@ -7719,7 +7719,7 @@
       sha256: 4a7bc5478a2ec8c5d186d63532eb22e75b79ba75ec3c0ce821676157318ef4ad
       uri: https://huggingface.co/ggml-org/Qwen2.5-Omni-7B-GGUF/resolve/main/mmproj-Qwen2.5-Omni-7B-Q8_0.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
@@ -10657,6 +10657,22 @@
     - filename: PKU-DS-LAB_FairyR1-32B-Q4_K_M.gguf
       sha256: bbfe6602b9d4f22da36090a4c77da0138c44daa4ffb01150d0370f6965503e65
       uri: huggingface://bartowski/PKU-DS-LAB_FairyR1-32B-GGUF/PKU-DS-LAB_FairyR1-32B-Q4_K_M.gguf
+- !!merge <<: *deepseek-r1
+  name: "nvidia_nemotron-research-reasoning-qwen-1.5b"
+  urls:
+    - https://huggingface.co/nvidia/Nemotron-Research-Reasoning-Qwen-1.5B
+    - https://huggingface.co/bartowski/nvidia_Nemotron-Research-Reasoning-Qwen-1.5B-GGUF
+  description: |
+    Nemotron-Research-Reasoning-Qwen-1.5B is the world’s leading 1.5B open-weight model for complex reasoning tasks such as mathematical problems, coding challenges, scientific questions, and logic puzzles. It is trained using the ProRL algorithm on a diverse and comprehensive set of datasets. Our model has achieved impressive results, outperforming Deepseek’s 1.5B model by a large margin on a broad range of tasks, including math, coding, and GPQA.
+
+    This model is for research and development only.
+  overrides:
+    parameters:
+      model: nvidia_Nemotron-Research-Reasoning-Qwen-1.5B-Q4_K_M.gguf
+  files:
+    - filename: nvidia_Nemotron-Research-Reasoning-Qwen-1.5B-Q4_K_M.gguf
+      sha256: 3685e223b41b39cef92aaa283d9cc943e27208eab942edfd1967059d6a98aa7a
+      uri: huggingface://bartowski/nvidia_Nemotron-Research-Reasoning-Qwen-1.5B-GGUF/nvidia_Nemotron-Research-Reasoning-Qwen-1.5B-Q4_K_M.gguf
 - &qwen2
   url: "github:mudler/LocalAI/gallery/chatml.yaml@master" ## Start QWEN2
   name: "qwen2-7b-instruct"