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EryriLabs/Lightning-Herald-30B-A3B-GGUF

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Model Card

Lightning-Herald-30B-A3B GGUF

<p align="center"> <img src="Lightning-Herald-30B-A3B.jpg" alt="Lightning-Herald" width="360"> </p>

GGUF builds of EryriLabs/Lightning-Herald-30B-A3B, my Hermes-Agent tune of NVIDIA Nemotron 3.5 Lightning (30B total, 3B active). The full model card, benchmarks and training details live on the main repo. This one is just the files.

Files

QuantSizeNotes
IQ4_XS19 GBThe exact file used in the before/after benchmark. Best fit for one 24GB card with a big context.
Q4KM25 GBStandard 4-bit. Needs two GPUs or some CPU offload on 24GB.
Q5KM27 GB
Q6_K35 GB
Q8_035 GBClose to lossless.

All made with llama.cpp b10413 (convert_hf_to_gguf.py then llama-quantize) from the released BF16 weights. You need a llama.cpp build with Nemotron-H support, so b10413 or newer.

Run

bash
llama-server -m Lightning-Herald-30B-A3B-IQ4_XS.gguf --jinja -ngl 999 -c 32768 --temp 1.0 --top-p 0.95

--jinja matters: it makes llama.cpp render the chat template with your tools and parse tool calls into structured tool_calls. The sampling above is NVIDIA's recommendation for the base model and what the benchmark used.

Point Hermes Agent at http://127.0.0.1:8080/v1. A config preset is on the main repo.

Licence

OpenMDW-1.1, inherited from the base. Training data was Apache 2.0.


Dwain Barnes, EryriLabs