Instructions to use burgasdotpro/Sebushka-llama-3.1-8B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use burgasdotpro/Sebushka-llama-3.1-8B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("burgasdotpro/Sebushka-llama-3.1-8B-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use burgasdotpro/Sebushka-llama-3.1-8B-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 burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf burgasdotpro/Sebushka-llama-3.1-8B-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 burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf burgasdotpro/Sebushka-llama-3.1-8B-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 burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf burgasdotpro/Sebushka-llama-3.1-8B-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 burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use burgasdotpro/Sebushka-llama-3.1-8B-GGUF with Ollama:
```
ollama run hf.co/burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use burgasdotpro/Sebushka-llama-3.1-8B-GGUF with Docker Model Runner:
```
docker model run hf.co/burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M
```

Lemonade

How to use burgasdotpro/Sebushka-llama-3.1-8B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull burgasdotpro/Sebushka-llama-3.1-8B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Sebushka-llama-3.1-8B-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

Модель на базе llama-3.1-8B с датасетом от знаменитой Сайги.

Uploaded model

Developed by: burgasdotpro
License: apache-2.0
Finetuned from model : unsloth/Meta-Llama-3.1-8B-bnb-4bit

Эта Meta-Llama-3.1-8B модель тренирована в 2 раза быстрей с помощью Unsloth и TRL библиотеки Huggingface

Downloads last month: 65

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

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Model tree for burgasdotpro/Sebushka-llama-3.1-8B-GGUF

Base model

meta-llama/Llama-3.1-8B

Quantized

unsloth/Meta-Llama-3.1-8B-bnb-4bit

Quantized

(236)

this model

Dataset used to train burgasdotpro/Sebushka-llama-3.1-8B-GGUF

Collection including burgasdotpro/Sebushka-llama-3.1-8B-GGUF

GGUF

Collection

GGUF models collection • 7 items • Updated Mar 2 • 1