Instructions to use Phonepadith/aidc-laollm-5k-based-qwen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use Phonepadith/aidc-laollm-5k-based-qwen with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("Phonepadith/aidc-laollm-5k-based-qwen") - llama-cpp-python
How to use Phonepadith/aidc-laollm-5k-based-qwen with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Phonepadith/aidc-laollm-5k-based-qwen", filename="aidc-laollm-5k-based-qwen-Q8.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Phonepadith/aidc-laollm-5k-based-qwen with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Phonepadith/aidc-laollm-5k-based-qwen # Run inference directly in the terminal: llama-cli -hf Phonepadith/aidc-laollm-5k-based-qwen
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Phonepadith/aidc-laollm-5k-based-qwen # Run inference directly in the terminal: llama-cli -hf Phonepadith/aidc-laollm-5k-based-qwen
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 Phonepadith/aidc-laollm-5k-based-qwen # Run inference directly in the terminal: ./llama-cli -hf Phonepadith/aidc-laollm-5k-based-qwen
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 Phonepadith/aidc-laollm-5k-based-qwen # Run inference directly in the terminal: ./build/bin/llama-cli -hf Phonepadith/aidc-laollm-5k-based-qwen
Use Docker
docker model run hf.co/Phonepadith/aidc-laollm-5k-based-qwen
- LM Studio
- Jan
- vLLM
How to use Phonepadith/aidc-laollm-5k-based-qwen with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Phonepadith/aidc-laollm-5k-based-qwen" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Phonepadith/aidc-laollm-5k-based-qwen", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Phonepadith/aidc-laollm-5k-based-qwen
- Ollama
How to use Phonepadith/aidc-laollm-5k-based-qwen with Ollama:
ollama run hf.co/Phonepadith/aidc-laollm-5k-based-qwen
- Unsloth Studio
How to use Phonepadith/aidc-laollm-5k-based-qwen 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 Phonepadith/aidc-laollm-5k-based-qwen 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 Phonepadith/aidc-laollm-5k-based-qwen to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Phonepadith/aidc-laollm-5k-based-qwen to start chatting
- Docker Model Runner
How to use Phonepadith/aidc-laollm-5k-based-qwen with Docker Model Runner:
docker model run hf.co/Phonepadith/aidc-laollm-5k-based-qwen
- Lemonade
How to use Phonepadith/aidc-laollm-5k-based-qwen with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Phonepadith/aidc-laollm-5k-based-qwen
Run and chat with the model
lemonade run user.aidc-laollm-5k-based-qwen-{{QUANT_TAG}}List all available models
lemonade list
llm.create_chat_completion(
messages = [
{
"role": "user",
"content": "What is the capital of France?"
}
]
)🧠 AIDC LLM ສຳລັບພາສາລາວ - ແລະ ສະຫລຸບຂໍ້ມູນ — Fine-tuned on AIDC-5K (Q8 GGUF)
This is a Lao language chat model based on Qwen/Qwen1.5-7B, fine-tuned on the AIDC 5K Lao prompt-completion dataset, and exported to GGUF format with Q8_0 quantization for fast inference using llama.cpp, LM Studio, or Ollama.
🧾 Model Summary
| Feature | Details |
|---|---|
| Base Model | Qwen1.5-7B |
| Fine-tuned By | Phonepadith Phoummavong |
| Language | Lao (lo) |
| Dataset | AIDC 5K Lao Prompt-Completion Dataset |
| Quantization | Q8_0 (8-bit, GGUF) |
| Format | GGUF |
| File Name | seallm-7b-lao-finetuned-lora-q8.gguf |
| Size (est.) | ~3–5 GB |
| License | apache-2.0 |
💡 Use Cases
- Lao chatbots or digital assistants
- Cultural and educational tools in Lao
- Research on low-resource language modeling
- Lao-native prompt generation and dialogue completion
📥 How to Use
🔸 LM Studio
- Download the
.ggufmodel file. - Open LM Studio.
- Click "Add Local Model".
- Load
aidc-laollm-5k-based-qwen-Q8.gguf.
🔸 Ollama
- Place the
.gguffile in your models directory. - Create a
Modelfile:FROM qwen:7b PARAMETER quantization=q8_0
- Downloads last month
- 11
We're not able to determine the quantization variants.
Model tree for Phonepadith/aidc-laollm-5k-based-qwen
Base model
Qwen/Qwen2.5-VL-7B-Instruct
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Phonepadith/aidc-laollm-5k-based-qwen", filename="", )