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 QuantFactory/Albatross2.1-8B-Instruct-GGUF:
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Albatross2.1-8B-Instruct-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/Albatross2.1-8B-Instruct-GGUF:
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/Albatross2.1-8B-Instruct-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 QuantFactory/Albatross2.1-8B-Instruct-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Albatross2.1-8B-Instruct-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 QuantFactory/Albatross2.1-8B-Instruct-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Albatross2.1-8B-Instruct-GGUF:
Use Docker
docker model run hf.co/QuantFactory/Albatross2.1-8B-Instruct-GGUF:
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QuantFactory/Albatross2.1-8B-Instruct-GGUF

This is quantized version of qingy2024/Albatross2.1-8B-Instruct created using llama.cpp

Original Model Card

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: qingy2024/NaturalLM3-8B-Instruct-v0.1
  - model: NousResearch/Hermes-3-Llama-3.1-8B
merge_method: slerp
base_model: qingy2024/NaturalLM3-8B-Instruct-v0.1
dtype: bfloat16
parameters:
  t: [0, 0.5, 1, 0.5, 0] # V shaped curve: Hermes for input & output, WizardMath in the middle layers
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GGUF
Model size
8B params
Architecture
llama
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