license: llama3
language:
- tr
pipeline_tag: text-generation
base_model: Metin/LLaMA-3-8B-Instruct-Abliterated-TR
tags: - llama-cpp
- gguf-my-repo
model-index: - name: LLaMA-3-8B-Instruct-Abliterated-TR
results:- task:
type: multiple-choice
dataset:
name: MMLU_TR_V0.2
type: multiple-choice
metrics:- type: 5-shot
value: 0.4908
name: 5-shot
verified: false - type: 0-shot
value: 0.4962
name: 0-shot
verified: false - type: 25-shot
value: 0.4377
name: 25-shot
verified: false - type: 10-shot
value: 0.4486
name: 10-shot
verified: false - type: 5-shot
value: 0.5323
name: 5-shot
verified: false - type: 5-shot
value: 0.5513
name: 5-shot
verified: false
- type: 5-shot
- task:
matrixportalx/LLaMA-3-8B-Instruct-Abliterated-TR-Q4_K_M-GGUF
This model was converted to GGUF format from Metin/LLaMA-3-8B-Instruct-Abliterated-TR 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 matrixportalx/LLaMA-3-8B-Instruct-Abliterated-TR-Q4_K_M-GGUF --hf-file llama-3-8b-instruct-abliterated-tr-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo matrixportalx/LLaMA-3-8B-Instruct-Abliterated-TR-Q4_K_M-GGUF --hf-file llama-3-8b-instruct-abliterated-tr-q4_k_m.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 matrixportalx/LLaMA-3-8B-Instruct-Abliterated-TR-Q4_K_M-GGUF --hf-file llama-3-8b-instruct-abliterated-tr-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo matrixportalx/LLaMA-3-8B-Instruct-Abliterated-TR-Q4_K_M-GGUF --hf-file llama-3-8b-instruct-abliterated-tr-q4_k_m.gguf -c 2048