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chore(model gallery): add nvidia_llama-3_3-nemotron-super-49b-v1 (#5041)

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2025-03-19 09:37:27 +01:00 • committed by GitHub
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gallery/index.yaml
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@ -1056,6 +1056,25 @@
- filename: ReadyArt_Forgotten-Safeword-70B-3.6-Q4_K_M.gguf
sha256: bd3a082638212064899db1afe29bf4c54104216e662ac6cc76722a21bf91967e
uri: huggingface://bartowski/ReadyArt_Forgotten-Safeword-70B-3.6-GGUF/ReadyArt_Forgotten-Safeword-70B-3.6-Q4_K_M.gguf
- !!merge <<: *llama33
name: "nvidia_llama-3_3-nemotron-super-49b-v1"
icon: https://cdn-avatars.huggingface.co/v1/production/uploads/1613114437487-60262a8e0703121c822a80b6.png
urls:
- https://huggingface.co/nvidia/Llama-3_3-Nemotron-Super-49B-v1
- https://huggingface.co/bartowski/nvidia_Llama-3_3-Nemotron-Super-49B-v1-GGUF
description: |
Llama-3.3-Nemotron-Super-49B-v1 is a large language model (LLM) which is a derivative of Meta Llama-3.3-70B-Instruct (AKA the reference model). It is a reasoning model that is post trained for reasoning, human chat preferences, and tasks, such as RAG and tool calling. The model supports a context length of 128K tokens.
Llama-3.3-Nemotron-Super-49B-v1 is a model which offers a great tradeoff between model accuracy and efficiency. Efficiency (throughput) directly translates to savings. Using a novel Neural Architecture Search (NAS) approach, we greatly reduce the model’s memory footprint, enabling larger workloads, as well as fitting the model on a single GPU at high workloads (H200). This NAS approach enables the selection of a desired point in the accuracy-efficiency tradeoff.
The model underwent a multi-phase post-training process to enhance both its reasoning and non-reasoning capabilities. This includes a supervised fine-tuning stage for Math, Code, Reasoning, and Tool Calling as well as multiple reinforcement learning (RL) stages using REINFORCE (RLOO) and Online Reward-aware Preference Optimization (RPO) algorithms for both chat and instruction-following. The final model checkpoint is obtained after merging the final SFT and Online RPO checkpoints. For more details on how the model was trained, please see this blog.
overrides:
parameters:
model: nvidia_Llama-3_3-Nemotron-Super-49B-v1-Q4_K_M.gguf
files:
- filename: nvidia_Llama-3_3-Nemotron-Super-49B-v1-Q4_K_M.gguf
sha256: d3fc12f4480cad5060f183d6c186ca47d800509224632bb22e15791711950524
uri: huggingface://bartowski/nvidia_Llama-3_3-Nemotron-Super-49B-v1-GGUF/nvidia_Llama-3_3-Nemotron-Super-49B-v1-Q4_K_M.gguf
- &rwkv
url: "github:mudler/LocalAI/gallery/rwkv.yaml@master"
name: "rwkv-6-world-7b"