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klyrone
/
Chimera

Text Generation
GGUF
mixtral
Mixture of Experts
mixture-of-experts
Merge
chimera
klyrone
instruct
Model card Files Files and versions
xet
Community

Instructions to use klyrone/Chimera with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • llama-cpp-python

    How to use klyrone/Chimera with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="klyrone/Chimera",
    	filename="Chimera-47B-Q5_K_M.gguf",
    )
    
    output = llm(
    	"Once upon a time,",
    	max_tokens=512,
    	echo=True
    )
    print(output)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • llama.cpp

    How to use klyrone/Chimera with llama.cpp:

    Install from brew
    brew install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf klyrone/Chimera:Q5_K_M
    # Run inference directly in the terminal:
    llama-cli -hf klyrone/Chimera:Q5_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf klyrone/Chimera:Q5_K_M
    # Run inference directly in the terminal:
    llama-cli -hf klyrone/Chimera:Q5_K_M
    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 klyrone/Chimera:Q5_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf klyrone/Chimera:Q5_K_M
    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 klyrone/Chimera:Q5_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf klyrone/Chimera:Q5_K_M
    Use Docker
    docker model run hf.co/klyrone/Chimera:Q5_K_M
  • LM Studio
  • Jan
  • vLLM

    How to use klyrone/Chimera with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "klyrone/Chimera"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "klyrone/Chimera",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/klyrone/Chimera:Q5_K_M
  • Ollama

    How to use klyrone/Chimera with Ollama:

    ollama run hf.co/klyrone/Chimera:Q5_K_M
  • Unsloth Studio new

    How to use klyrone/Chimera with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for klyrone/Chimera to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for klyrone/Chimera to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for klyrone/Chimera to start chatting
  • Docker Model Runner

    How to use klyrone/Chimera with Docker Model Runner:

    docker model run hf.co/klyrone/Chimera:Q5_K_M
  • Lemonade

    How to use klyrone/Chimera with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull klyrone/Chimera:Q5_K_M
    Run and chat with the model
    lemonade run user.Chimera-Q5_K_M
    List all available models
    lemonade list
Chimera
Ctrl+K
Ctrl+K
  • 1 contributor
History: 23 commits
kk497055's picture
kk497055
Add quantitative benchmarks to model card from paper
d9984b3 verified about 19 hours ago
  • .gitattributes
    1.93 kB
    Upload Modular Expert Assembly (MEA)_ Zero-Compute Capability Transfer in Mixture-of-Experts Architectures.pdf about 2 months ago
  • Chimera-47B-Q5_K_M.gguf
    33.2 GB
    xet
    Rename to Chimera-47B-Q5_K_M.gguf 2 months ago
  • Modular Expert Assembly (MEA)_ Zero-Compute Capability Transfer in Mixture-of-Experts Architectures.pdf
    150 kB
    xet
    Upload Modular Expert Assembly (MEA)_ Zero-Compute Capability Transfer in Mixture-of-Experts Architectures.pdf with huggingface_hub 16 days ago
  • README.md
    10.3 kB
    Add quantitative benchmarks to model card from paper about 19 hours ago
  • config.json
    411 Bytes
    Add correct Mixtral config.json for lm-eval about 2 months ago