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Llama-3_1-Nemotron-51B-Instruct-GGUF

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metadata
library_name: transformers
pipeline_tag: text-generation
language:
  - en
tags:
  - nvidia
  - llama-3
  - pytorch
  - TensorBlock
  - GGUF
license: other
license_name: nvidia-open-model-license
license_link: >-
  https://developer.download.nvidia.com/licenses/nvidia-open-model-license-agreement-june-2024.pdf
base_model: nvidia/Llama-3_1-Nemotron-51B-Instruct
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nvidia/Llama-3_1-Nemotron-51B-Instruct - GGUF

This repo contains GGUF format model files for nvidia/Llama-3_1-Nemotron-51B-Instruct.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4391.

Prompt template 

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 26 Jul 2024

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Model file specification

Filename Quant type File Size Description
Llama-3_1-Nemotron-51B-Instruct-Q2_K.gguf Q2_K 19.419 GB smallest, significant quality loss - not recommended for most purposes
Llama-3_1-Nemotron-51B-Instruct-Q3_K_S.gguf Q3_K_S 22.652 GB very small, high quality loss
Llama-3_1-Nemotron-51B-Instruct-Q3_K_M.gguf Q3_K_M 25.182 GB very small, high quality loss
Llama-3_1-Nemotron-51B-Instruct-Q3_K_L.gguf Q3_K_L 27.350 GB small, substantial quality loss
Llama-3_1-Nemotron-51B-Instruct-Q4_0.gguf Q4_0 29.252 GB legacy; small, very high quality loss - prefer using Q3_K_M
Llama-3_1-Nemotron-51B-Instruct-Q4_K_S.gguf Q4_K_S 29.484 GB small, greater quality loss
Llama-3_1-Nemotron-51B-Instruct-Q4_K_M.gguf Q4_K_M 31.037 GB medium, balanced quality - recommended
Llama-3_1-Nemotron-51B-Instruct-Q5_0.gguf Q5_0 35.559 GB legacy; medium, balanced quality - prefer using Q4_K_M
Llama-3_1-Nemotron-51B-Instruct-Q5_K_S.gguf Q5_K_S 35.559 GB large, low quality loss - recommended
Llama-3_1-Nemotron-51B-Instruct-Q5_K_M.gguf Q5_K_M 36.465 GB large, very low quality loss - recommended
Llama-3_1-Nemotron-51B-Instruct-Q6_K.gguf Q6_K 42.259 GB very large, extremely low quality loss
Llama-3_1-Nemotron-51B-Instruct-Q8_0 Q8_0 54.731 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/Llama-3_1-Nemotron-51B-Instruct-GGUF --include "Llama-3_1-Nemotron-51B-Instruct-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/Llama-3_1-Nemotron-51B-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'