Instructions to use dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B 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 dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16
# Run inference directly in the terminal:
llama cli -hf dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16
# Run inference directly in the terminal:
llama cli -hf dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B: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 dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16
# Run inference directly in the terminal:
./llama-cli -hf dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B: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 dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16

Use Docker

docker model run hf.co/dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16

LM Studio
Jan
Ollama
How to use dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B with Ollama:
```
ollama run hf.co/dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16
```
Unsloth Desktop
Docker Model Runner
How to use dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B with Docker Model Runner:
```
docker model run hf.co/dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16
```

Lemonade

How to use dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull dat-lequoc/fast-apply_gguf-16bit_0-v0.12-7B:F16

Run and chat with the model

lemonade run user.fast-apply_gguf-16bit_0-v0.12-7B-F16

List all available models

lemonade list

Atomic Chat

fast-apply_gguf-16bit_0-v0.12-7B / config.json

LE Quoc Dat

(Trained with Unsloth)

3b06bcc verified almost 2 years ago

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	{
	"model_type": "qwen2"
	}