metadata
base_model: crestf411/gemma2-9B-sunfall-v0.5
library_name: transformers
license: gemma
pipeline_tag: text-generation
tags:
- conversational
- llama-cpp
- gguf-my-repo
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: >-
To access Gemma on Hugging Face, you’re required to review and agree to
Google’s usage license. To do this, please ensure you’re logged in to Hugging
Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
NikolayKozloff/gemma2-9B-sunfall-v0.5-Q8_0-GGUF
This model was converted to GGUF format from crestf411/gemma2-9B-sunfall-v0.5
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 NikolayKozloff/gemma2-9B-sunfall-v0.5-Q8_0-GGUF --hf-file gemma2-9b-sunfall-v0.5-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo NikolayKozloff/gemma2-9B-sunfall-v0.5-Q8_0-GGUF --hf-file gemma2-9b-sunfall-v0.5-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 NikolayKozloff/gemma2-9B-sunfall-v0.5-Q8_0-GGUF --hf-file gemma2-9b-sunfall-v0.5-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo NikolayKozloff/gemma2-9B-sunfall-v0.5-Q8_0-GGUF --hf-file gemma2-9b-sunfall-v0.5-q8_0.gguf -c 2048