Instructions to use Kquant03/ResplendentAI-Flora_7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Kquant03/ResplendentAI-Flora_7B-GGUF with Transformers:

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Kquant03/ResplendentAI-Flora_7B-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Kquant03/ResplendentAI-Flora_7B-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -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 serve -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

LM Studio
Jan
Ollama
How to use Kquant03/ResplendentAI-Flora_7B-GGUF with Ollama:
```
ollama run hf.co/Kquant03/ResplendentAI-Flora_7B-GGUF
```
Unsloth Desktop
Docker Model Runner
How to use Kquant03/ResplendentAI-Flora_7B-GGUF with Docker Model Runner:
```
docker model run hf.co/Kquant03/ResplendentAI-Flora_7B-GGUF
```

Lemonade

How to use Kquant03/ResplendentAI-Flora_7B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Kquant03/ResplendentAI-Flora_7B-GGUF

Run and chat with the model

lemonade run user.ResplendentAI-Flora_7B-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

Flora

(created by ResplendentAI, quantized by me)

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

Downloads last month: 55

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

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Model tree for Kquant03/ResplendentAI-Flora_7B-GGUF

Base model

jeiku/FloraBase

Quantized

(3)

this model

Kquant03
/

ResplendentAI-Flora_7B-GGUF

Flora

Configuration

Model tree for Kquant03/ResplendentAI-Flora_7B-GGUF

Dataset used to train Kquant03/ResplendentAI-Flora_7B-GGUF