How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf nold/Prima-Pastacles-7b-GGUF:
# Run inference directly in the terminal:
llama-cli -hf nold/Prima-Pastacles-7b-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf nold/Prima-Pastacles-7b-GGUF:
# Run inference directly in the terminal:
llama-cli -hf nold/Prima-Pastacles-7b-GGUF:
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 nold/Prima-Pastacles-7b-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf nold/Prima-Pastacles-7b-GGUF:
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 nold/Prima-Pastacles-7b-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf nold/Prima-Pastacles-7b-GGUF:
Use Docker
docker model run hf.co/nold/Prima-Pastacles-7b-GGUF:
Quick Links

image/jpeg Quants Thanks to @Nold and @Bartowski:

https://huggingface.co/nold/Prima-Pastacles-7b-GGUF

https://huggingface.co/bartowski/Prima-Pastacles-7b-exl2

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: Test157t/Pasta-PrimaMaid-7b
        layer_range: [0, 32]
      - model: Locutusque/Hercules-2.5-Mistral-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: Test157t/Pasta-PrimaMaid-7b
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

Quantization of Model Test157t/Prima-Pastacles-7b. Created using llm-quantizer Pipeline

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GGUF
Model size
7B params
Architecture
llama
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