base_model, language, library_name, license, pipeline_tag, tags, widget, model-index

base_model	language	library_name	license	pipeline_tag	tags	widget	model-index
NousResearch/Hermes-4-14B	en	transformers	apache-2.0	text-generation	Qwen-3-14B instruct finetune reasoning hybrid-mode chatml function calling tool use json mode structured outputs atropos dataforge long context roleplaying chat llama-cpp gguf-my-repo	example_title messages Hermes 4 role content system You are Hermes 4, a capable, neutrally-aligned assistant. Prefer concise, correct answers. role content user Explain the difference between BFS and DFS to a new CS student.	name results Hermes-4-Qwen-3-14B

gnigguhface/Hermes-4-14B-Q8_0-GGUF

This model was converted to GGUF format from NousResearch/Hermes-4-14B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo gnigguhface/Hermes-4-14B-Q8_0-GGUF --hf-file hermes-4-14b-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo gnigguhface/Hermes-4-14B-Q8_0-GGUF --hf-file hermes-4-14b-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo gnigguhface/Hermes-4-14B-Q8_0-GGUF --hf-file hermes-4-14b-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo gnigguhface/Hermes-4-14B-Q8_0-GGUF --hf-file hermes-4-14b-q8_0.gguf -c 2048