Instructions to use IzzatilloAI/LLamA-3.1-8B-Uz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IzzatilloAI/LLamA-3.1-8B-Uz with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("IzzatilloAI/LLamA-3.1-8B-Uz", dtype="auto")

llama-cpp-python

How to use IzzatilloAI/LLamA-3.1-8B-Uz with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="IzzatilloAI/LLamA-3.1-8B-Uz",
	filename="unsloth.F16.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use IzzatilloAI/LLamA-3.1-8B-Uz 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 IzzatilloAI/LLamA-3.1-8B-Uz:F16
# Run inference directly in the terminal:
llama cli -hf IzzatilloAI/LLamA-3.1-8B-Uz:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf IzzatilloAI/LLamA-3.1-8B-Uz:F16
# Run inference directly in the terminal:
llama cli -hf IzzatilloAI/LLamA-3.1-8B-Uz:F16

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 IzzatilloAI/LLamA-3.1-8B-Uz:F16
# Run inference directly in the terminal:
./llama-cli -hf IzzatilloAI/LLamA-3.1-8B-Uz:F16

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 IzzatilloAI/LLamA-3.1-8B-Uz:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf IzzatilloAI/LLamA-3.1-8B-Uz:F16

Use Docker

docker model run hf.co/IzzatilloAI/LLamA-3.1-8B-Uz:F16

LM Studio
Jan
Ollama
How to use IzzatilloAI/LLamA-3.1-8B-Uz with Ollama:
```
ollama run hf.co/IzzatilloAI/LLamA-3.1-8B-Uz:F16
```

Unsloth Studio

How to use IzzatilloAI/LLamA-3.1-8B-Uz with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for IzzatilloAI/LLamA-3.1-8B-Uz to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for IzzatilloAI/LLamA-3.1-8B-Uz to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for IzzatilloAI/LLamA-3.1-8B-Uz to start chatting

Atomic Chat new
Docker Model Runner
How to use IzzatilloAI/LLamA-3.1-8B-Uz with Docker Model Runner:
```
docker model run hf.co/IzzatilloAI/LLamA-3.1-8B-Uz:F16
```

Lemonade

How to use IzzatilloAI/LLamA-3.1-8B-Uz with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull IzzatilloAI/LLamA-3.1-8B-Uz:F16

Run and chat with the model

lemonade run user.LLamA-3.1-8B-Uz-F16

List all available models

lemonade list

Uzbek General Language Model

This model is a fine-tuned version of the LLama-3.1-8B model, specifically adapted for general-purpose natural language understanding and generation in Uzbek. The model has undergone general fine-tuning using a diverse dataset comprising Uzbek text from Wikipedia, news articles, and books. It is designed to support a wide range of applications such as question-answering, summarization, text generation, and more in the Uzbek language.

Developed by: Izzatillo Yuldashev
License: apache-2.0
Fine-tuned from model : meta-llama/Llama-3.1-8B

Downloads last month: 1

Safetensors

Model size

8B params

Tensor type

BF16

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