README.md · Triangle104/L3.1-8B-sunfall-stheno-v0.6.1-Q4_K

metadata

base_model: crestf411/L3.1-8B-sunfall-stheno-v0.6.1
datasets:
  - crestf411/LimaRP-DS
  - AI-MO/NuminaMath-CoT
library_name: transformers
license: llama3
license_name: llama3
license_link: LICENSE
tags:
  - not-for-all-audiences
  - llama-cpp
  - gguf-my-repo

This model was converted to GGUF format from crestf411/L3.1-8B-sunfall-stheno-v0.6.1 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

From original model:

Sunfall (2024-07-31) v0.6.1 on top of https://huggingface.co/Sao10K/Llama-3.1-8B-Stheno-v3.4

See https://huggingface.co/crestf411/L3.1-8B-sunfall-v0.6.1-dpo for details on usage.

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/L3.1-8B-sunfall-stheno-v0.6.1-Q4_K_M-GGUF --hf-file l3.1-8b-sunfall-stheno-v0.6.1-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/L3.1-8B-sunfall-stheno-v0.6.1-Q4_K_M-GGUF --hf-file l3.1-8b-sunfall-stheno-v0.6.1-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 Triangle104/L3.1-8B-sunfall-stheno-v0.6.1-Q4_K_M-GGUF --hf-file l3.1-8b-sunfall-stheno-v0.6.1-q4_k_m.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo Triangle104/L3.1-8B-sunfall-stheno-v0.6.1-Q4_K_M-GGUF --hf-file l3.1-8b-sunfall-stheno-v0.6.1-q4_k_m.gguf -c 2048