Instructions to use ksjpswaroop/CleverOfficeGPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use ksjpswaroop/CleverOfficeGPT with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="ksjpswaroop/CleverOfficeGPT", filename="cleverOfficeGPT-1.5b-fp16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ksjpswaroop/CleverOfficeGPT with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ksjpswaroop/CleverOfficeGPT # Run inference directly in the terminal: llama-cli -hf ksjpswaroop/CleverOfficeGPT
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf ksjpswaroop/CleverOfficeGPT # Run inference directly in the terminal: llama-cli -hf ksjpswaroop/CleverOfficeGPT
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 ksjpswaroop/CleverOfficeGPT # Run inference directly in the terminal: ./llama-cli -hf ksjpswaroop/CleverOfficeGPT
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 ksjpswaroop/CleverOfficeGPT # Run inference directly in the terminal: ./build/bin/llama-cli -hf ksjpswaroop/CleverOfficeGPT
Use Docker
docker model run hf.co/ksjpswaroop/CleverOfficeGPT
- LM Studio
- Jan
- Ollama
How to use ksjpswaroop/CleverOfficeGPT with Ollama:
ollama run hf.co/ksjpswaroop/CleverOfficeGPT
- Unsloth Studio
How to use ksjpswaroop/CleverOfficeGPT 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 ksjpswaroop/CleverOfficeGPT 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 ksjpswaroop/CleverOfficeGPT to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ksjpswaroop/CleverOfficeGPT to start chatting
- Docker Model Runner
How to use ksjpswaroop/CleverOfficeGPT with Docker Model Runner:
docker model run hf.co/ksjpswaroop/CleverOfficeGPT
- Lemonade
How to use ksjpswaroop/CleverOfficeGPT with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ksjpswaroop/CleverOfficeGPT
Run and chat with the model
lemonade run user.CleverOfficeGPT-{{QUANT_TAG}}List all available models
lemonade list
Upload 5 files
Browse files- .gitattributes +1 -0
- cleverOfficeGPT-1.5b-fp16.gguf +3 -0
- params +11 -0
- system +1 -0
- template +6 -0
.gitattributes
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cleverOfficeGPT-1.5b-fp16.gguf filter=lfs diff=lfs merge=lfs -text
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cleverOfficeGPT-1.5b-fp16.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:5f7555a5804e14d918aadd73518567affcf29fcec23f9a992dd2353fea8d0249
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size 3560413856
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params
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{
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"num_ctx": 32768,
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"num_predict": 2048,
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"stop": [
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"<|im_end|>",
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"<|im_start|>"
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],
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"temperature": 0.5,
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"top_k": 45,
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"top_p": 0.95
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system
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You are a clever, unbiased, uncensored, and helpful AI assistant for Office operations.
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template
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{{ if .System }}<|im_start|>system
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{{ .System }}<|im_end|>
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{{ end }}{{ if .Prompt }}<|im_start|>user
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{{ .Prompt }}<|im_end|>
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{{ end }}<|im_start|>assistant
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{{ .Response }}<|im_end|>
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