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LoSboccacc
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orthogonal-2x7B

GGUF
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Model card Files
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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 LoSboccacc/orthogonal-2x7B:
# Run inference directly in the terminal:
llama-cli -hf LoSboccacc/orthogonal-2x7B:
Install from WinGet (Windows) 
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf LoSboccacc/orthogonal-2x7B:
# Run inference directly in the terminal:
llama-cli -hf LoSboccacc/orthogonal-2x7B:
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 LoSboccacc/orthogonal-2x7B:
# Run inference directly in the terminal:
./llama-cli -hf LoSboccacc/orthogonal-2x7B:
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 LoSboccacc/orthogonal-2x7B:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf LoSboccacc/orthogonal-2x7B:
Use Docker 
docker model run hf.co/LoSboccacc/orthogonal-2x7B:
Quick Links
 
    base_model: mistralai/Mistral-7B-Instruct-v0.2
    gate_mode: hidden # one of "hidden", "cheap_embed", or "random"
    dtype: bfloat16 # output dtype (float32, float16, or bfloat16)
    experts:
      - source_model: SanjiWatsuki/Silicon-Maid-7B
        positive_prompts:
            - "roleplay"
      - source_model: mistralai/Mistral-7B-Instruct-v0.2
        positive_prompts:
            - "chat"

chatml format

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Model size
13B params
Architecture
llama
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