metadata
library_name: transformers
license: other
license_name: nvidia-open-model-license
license_link: >-
https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
pipeline_tag: text-generation
language:
- en
tags:
- nvidia
- reasoning
- math
- reinforcement learning
- pytorch
- TensorBlock
- GGUF
base_model: nvidia/AceMath-RL-Nemotron-7B
nvidia/AceMath-RL-Nemotron-7B - GGUF
This repo contains GGUF format model files for nvidia/AceMath-RL-Nemotron-7B.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.
Our projects
| Awesome MCP Servers | TensorBlock Studio |
|---|---|
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| A comprehensive collection of Model Context Protocol (MCP) servers. | A lightweight, open, and extensible multi-LLM interaction studio. |
| 👀 See what we built 👀 | 👀 See what we built 👀 |
Prompt template
<｜begin▁of▁sentence｜>{system_prompt}<｜User｜>{prompt}<｜Assistant｜><think>
Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| AceMath-RL-Nemotron-7B-Q2_K.gguf | Q2_K | 3.016 GB | smallest, significant quality loss - not recommended for most purposes |
| AceMath-RL-Nemotron-7B-Q3_K_S.gguf | Q3_K_S | 3.492 GB | very small, high quality loss |
| AceMath-RL-Nemotron-7B-Q3_K_M.gguf | Q3_K_M | 3.808 GB | very small, high quality loss |
| AceMath-RL-Nemotron-7B-Q3_K_L.gguf | Q3_K_L | 4.088 GB | small, substantial quality loss |
| AceMath-RL-Nemotron-7B-Q4_0.gguf | Q4_0 | 4.431 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| AceMath-RL-Nemotron-7B-Q4_K_S.gguf | Q4_K_S | 4.458 GB | small, greater quality loss |
| AceMath-RL-Nemotron-7B-Q4_K_M.gguf | Q4_K_M | 4.683 GB | medium, balanced quality - recommended |
| AceMath-RL-Nemotron-7B-Q5_0.gguf | Q5_0 | 5.315 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| AceMath-RL-Nemotron-7B-Q5_K_S.gguf | Q5_K_S | 5.315 GB | large, low quality loss - recommended |
| AceMath-RL-Nemotron-7B-Q5_K_M.gguf | Q5_K_M | 5.445 GB | large, very low quality loss - recommended |
| AceMath-RL-Nemotron-7B-Q6_K.gguf | Q6_K | 6.254 GB | very large, extremely low quality loss |
| AceMath-RL-Nemotron-7B-Q8_0.gguf | Q8_0 | 8.099 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/nvidia_AceMath-RL-Nemotron-7B-GGUF --include "AceMath-RL-Nemotron-7B-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/nvidia_AceMath-RL-Nemotron-7B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'