Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf bigbossmonster/output:Q6_K# Run inference directly in the terminal:
llama-cli -hf bigbossmonster/output:Q6_KUse 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 bigbossmonster/output:Q6_K# Run inference directly in the terminal:
./llama-cli -hf bigbossmonster/output:Q6_KBuild 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 bigbossmonster/output:Q6_K# Run inference directly in the terminal:
./build/bin/llama-cli -hf bigbossmonster/output:Q6_KUse Docker
docker model run hf.co/bigbossmonster/output:Q6_KYAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
This directory includes a few sample datasets to get you started.
california_housing_data*.csvis California housing data from the 1990 US Census; more information is available at: https://docs.google.com/document/d/e/2PACX-1vRhYtsvc5eOR2FWNCwaBiKL6suIOrxJig8LcSBbmCbyYsayia_DvPOOBlXZ4CAlQ5nlDD8kTaIDRwrN/pubmnist_*.csvis a small sample of the MNIST database, which is described at: http://yann.lecun.com/exdb/mnist/anscombe.jsoncontains a copy of Anscombe's quartet; it was originally described inAnscombe, F. J. (1973). 'Graphs in Statistical Analysis'. American Statistician. 27 (1): 17-21. JSTOR 2682899.
and our copy was prepared by the vega_datasets library.
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Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf bigbossmonster/output:Q6_K# Run inference directly in the terminal: llama-cli -hf bigbossmonster/output:Q6_K