Transformers
GGUF
English
finetune
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 Kquant03/ResplendentAI-Flora_7B-GGUF
# Run inference directly in the terminal:
llama-cli -hf Kquant03/ResplendentAI-Flora_7B-GGUF
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Kquant03/ResplendentAI-Flora_7B-GGUF
# Run inference directly in the terminal:
llama-cli -hf Kquant03/ResplendentAI-Flora_7B-GGUF
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 Kquant03/ResplendentAI-Flora_7B-GGUF
# Run inference directly in the terminal:
./llama-cli -hf Kquant03/ResplendentAI-Flora_7B-GGUF
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 Kquant03/ResplendentAI-Flora_7B-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Kquant03/ResplendentAI-Flora_7B-GGUF
Use Docker
docker model run hf.co/Kquant03/ResplendentAI-Flora_7B-GGUF
Quick Links

Flora

(created by ResplendentAI, quantized by me)

image/jpeg

Configuration

The following YAML configuration was used to produce this model:

merge_method: linear
models:
  - model: jeiku/FloraBase+jeiku/Synthetic_Soul_1k_Mistral_128
    parameters:
      weight: 1       
dtype: float16
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GGUF
Model size
7B params
Architecture
llama
Hardware compatibility
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Model tree for Kquant03/ResplendentAI-Flora_7B-GGUF

Base model

jeiku/FloraBase
Quantized
(3)
this model

Dataset used to train Kquant03/ResplendentAI-Flora_7B-GGUF