Instructions to use eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-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 eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_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 eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_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 eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M

Use Docker

docker model run hf.co/eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf with Ollama:
```
ollama run hf.co/eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf with Docker Model Runner:
```
docker model run hf.co/eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M
```

Lemonade

How to use eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull eigenben/llama-3-8b-bnb-4bit-alpaca-finetuned-gguf:Q4_K_M

Run and chat with the model

lemonade run user.llama-3-8b-bnb-4bit-alpaca-finetuned-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

llama-3-8b-bnb-4bit-alpaca-finetuned-gguf / llama-3-8b.Q4_K_M.gguf

eigenben

Trained with Unsloth

bad6857 verified 9 months ago

Download

History Blame GGUF Editor new Delete

4.92 GB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: d1d376e9ee6d4ea7a4c397f3bb43b3b73bc5fe2cc160805f456f5d8281b51e43
Size of remote file:: 4.92 GB
SHA256:: a920ffaab6f9f59227519daa7713f07e6d55171362fe410c5953ac32d4f7f385

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.