Instructions to use risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF with Transformers:

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-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 risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0

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 risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0

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 risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0

LM Studio
Jan
Ollama
How to use risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF with Ollama:
```
ollama run hf.co/risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0
```
Unsloth Desktop
Docker Model Runner
How to use risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0
```

Lemonade

How to use risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF-Q8_0

List all available models

lemonade list

Atomic Chat

Betawi Language Model: Bokap Betawi-7B

Bokap Betawi is a language model fine-tuned from Qwen 2.5 7B on 1,000 instruction-output pairs synthetic Betawi language dataset generated using GPT-4o. This model is specifically made to enhance the performance of tasks in bahasa Betawi.

Version Alpha

This model was converted to GGUF format from risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model. See here for another version:

Version	URL
fp16	Bokap-Betawi-v0-Qwen2.5-7B-fp16
4bit	Bokap-Betawi-v0-Qwen2.5-7B-4bit
GGUF	Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF --hf-file bokap-betawi-v0-qwen2.5-7b-fp16-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF --hf-file bokap-betawi-v0-qwen2.5-7b-fp16-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF --hf-file bokap-betawi-v0-qwen2.5-7b-fp16-q8_0.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF --hf-file bokap-betawi-v0-qwen2.5-7b-fp16-q8_0.gguf -c 2048

Description

Developed by: Risang Panggalih
Finetuned from model: Qwen 2.5 7B

Downloads last month: 26

GGUF

Model size

8B params

Architecture

qwen2

Hardware compatibility

8-bit

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Model tree for risangpanggalih/Bokap-Betawi-v0-Qwen2.5-7B-fp16-Q8_0-GGUF

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Lingos

Collection

Large Language Model(s), NLP, etc • 3 items • Updated Apr 30, 2025