Instructions to use Aliguinga01/rule_violation2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Aliguinga01/rule_violation2 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Aliguinga01/rule_violation2",
	filename="llama.cpp/models/ggml-vocab-aquila.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Aliguinga01/rule_violation2 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Aliguinga01/rule_violation2:F16
# Run inference directly in the terminal:
llama-cli -hf Aliguinga01/rule_violation2:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Aliguinga01/rule_violation2:F16
# Run inference directly in the terminal:
llama-cli -hf Aliguinga01/rule_violation2: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 Aliguinga01/rule_violation2:F16
# Run inference directly in the terminal:
./llama-cli -hf Aliguinga01/rule_violation2: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 Aliguinga01/rule_violation2:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Aliguinga01/rule_violation2:F16

Use Docker

docker model run hf.co/Aliguinga01/rule_violation2:F16

LM Studio
Jan
Ollama
How to use Aliguinga01/rule_violation2 with Ollama:
```
ollama run hf.co/Aliguinga01/rule_violation2:F16
```

Unsloth Studio new

How to use Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 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 Aliguinga01/rule_violation2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Aliguinga01/rule_violation2 to start chatting

Docker Model Runner
How to use Aliguinga01/rule_violation2 with Docker Model Runner:
```
docker model run hf.co/Aliguinga01/rule_violation2:F16
```

Lemonade

How to use Aliguinga01/rule_violation2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Aliguinga01/rule_violation2:F16

Run and chat with the model

lemonade run user.rule_violation2-F16

List all available models

lemonade list

rule_violation2 / llama.cpp /.devops /nix /scope.nix

Aliguinga01

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	{
	lib,
	newScope,
	python3,
	llamaVersion ? "0.0.0",
	}:

	let
	pythonPackages = python3.pkgs;
	buildPythonPackage = pythonPackages.buildPythonPackage;
	numpy = pythonPackages.numpy;
	tqdm = pythonPackages.tqdm;
	sentencepiece = pythonPackages.sentencepiece;
	pyyaml = pythonPackages.pyyaml;
	poetry-core = pythonPackages.poetry-core;
	pytestCheckHook = pythonPackages.pytestCheckHook;
	in

	# We're using `makeScope` instead of just writing out an attrset
	# because it allows users to apply overlays later using `overrideScope'`.
	# Cf. https://noogle.dev/f/lib/makeScope

	lib.makeScope newScope (self: {
	inherit llamaVersion;
	gguf-py = self.callPackage ./package-gguf-py.nix {
	inherit
	buildPythonPackage
	numpy
	tqdm
	sentencepiece
	poetry-core
	pyyaml
	pytestCheckHook
	;
	};
	python-scripts = self.callPackage ./python-scripts.nix { inherit buildPythonPackage poetry-core; };
	llama-cpp = self.callPackage ./package.nix { };
	docker = self.callPackage ./docker.nix { };
	docker-min = self.callPackage ./docker.nix { interactive = false; };
	sif = self.callPackage ./sif.nix { };
	})