Instructions to use shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test 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 shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test
# Run inference directly in the terminal:
llama cli -hf shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test
# Run inference directly in the terminal:
llama cli -hf shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test

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 shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test
# Run inference directly in the terminal:
./llama-cli -hf shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test

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 shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test
# Run inference directly in the terminal:
./build/bin/llama-cli -hf shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test

Use Docker

docker model run hf.co/shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test

LM Studio
Jan
Ollama
How to use shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test with Ollama:
```
ollama run hf.co/shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test
```
Unsloth Desktop
Docker Model Runner
How to use shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test with Docker Model Runner:
```
docker model run hf.co/shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test
```

Lemonade

How to use shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test

Run and chat with the model

lemonade run user.Llama-3.2-3B_Instruct_Indonesian_gguf-test-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

Finetuned Llama-3.2-3B with MBZUAI-Bactrian-X Indonesian datasets only

Copal_id benchmark (before quantized into gguf):

copal_id_standard = Formal Language

copal_id_standard_multishots	Result
0-shot	56
10-shots	58
25-shots	57

copal_id_colloquial = Informal Language and local nuances

copal_id_colloquial_multishots	Result
0-shot	54
10-shots	54
25-shots	52

Using Unsloth.ai for finetuning

Downloads last month: 28

GGUF

Model size

3B params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

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Model tree for shiningdota/Llama-3.2-3B_Instruct_Indonesian_gguf-test

Base model

meta-llama/Llama-3.2-3B

Quantized

(157)

this model

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Llama-3.2-3B_Instruct_Indonesian_gguf-test

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