Transformers
GGUF
English
llama-cpp
gguf-my-repo
Inference Endpoints
conversational
Triangle104's picture
Upload README.md with huggingface_hub
49a231d verified
|
raw
history blame
1.97 kB
metadata
base_model: nothingiisreal/MN-12B-Celeste-V1.9
datasets:
  - nothingiisreal/c2-logs-cleaned
  - kalomaze/Opus_Instruct_25k
  - nothingiisreal/Reddit-Dirty-And-WritingPrompts
language:
  - en
library_name: transformers
license: apache-2.0
tags:
  - llama-cpp
  - gguf-my-repo

Triangle104/MN-12B-Celeste-V1.9-Q8_0-GGUF

This model was converted to GGUF format from nothingiisreal/MN-12B-Celeste-V1.9 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 Triangle104/MN-12B-Celeste-V1.9-Q8_0-GGUF --hf-file mn-12b-celeste-v1.9-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/MN-12B-Celeste-V1.9-Q8_0-GGUF --hf-file mn-12b-celeste-v1.9-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 Triangle104/MN-12B-Celeste-V1.9-Q8_0-GGUF --hf-file mn-12b-celeste-v1.9-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/MN-12B-Celeste-V1.9-Q8_0-GGUF --hf-file mn-12b-celeste-v1.9-q8_0.gguf -c 2048