How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
# Run inference directly in the terminal:
llama cli -hf Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
# Run inference directly in the terminal:
llama cli -hf Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
# Run inference directly in the terminal:
./llama-cli -hf Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
Use Docker
docker model run hf.co/Wonderlab-Testing-Grounds/Interferon-lambda-RP-9B-Preview-2608:
Quick Links

One of the many testing version for my upcoming Nyx-RP-9B-Instruct-2608-v2, this one had its stability improved after I carefully analyzed the first versions.

Training details:

Method: LoRA

  • Rank: 226
  • Epochs: 2(decreased from previous 3, which did seem to be the breaking point)

Hardware used for training(I have patience):

  • RTX 5070 Ti
  • R7800X3D + 32gb DDR5

Dataset detail:

Its a fairly new dataset which I gathered from the best RP logs I had on my hands, it included a lot of explicit long turn conversations so keep in mind the reduced refusals.

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