How to use from
OpenClaw
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantFactory/Albatross2.1-8B-Instruct-GGUF:
Configure OpenClaw
# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "QuantFactory/Albatross2.1-8B-Instruct-GGUF:" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
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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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