nsfw

roleplay

español

4-bit precision

Llama 3.2

Not-For-All-Audiences

imatrix

conversational

Model card Files Files and versions

xet

Community

Instructions to use Novaciano/Magnum-1b_Aesir-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

llama-cpp-python

How to use Novaciano/Magnum-1b_Aesir-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Novaciano/Magnum-1b_Aesir-GGUF",
	filename="Magnum-1b_Aesir.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Novaciano/Magnum-1b_Aesir-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Novaciano/Magnum-1b_Aesir-GGUF
# Run inference directly in the terminal:
llama-cli -hf Novaciano/Magnum-1b_Aesir-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Novaciano/Magnum-1b_Aesir-GGUF
# Run inference directly in the terminal:
llama-cli -hf Novaciano/Magnum-1b_Aesir-GGUF

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 Novaciano/Magnum-1b_Aesir-GGUF
# Run inference directly in the terminal:
./llama-cli -hf Novaciano/Magnum-1b_Aesir-GGUF

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 Novaciano/Magnum-1b_Aesir-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Novaciano/Magnum-1b_Aesir-GGUF

Use Docker

docker model run hf.co/Novaciano/Magnum-1b_Aesir-GGUF

LM Studio
Jan
Ollama
How to use Novaciano/Magnum-1b_Aesir-GGUF with Ollama:
```
ollama run hf.co/Novaciano/Magnum-1b_Aesir-GGUF
```

Unsloth Studio

How to use Novaciano/Magnum-1b_Aesir-GGUF 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 Novaciano/Magnum-1b_Aesir-GGUF 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 Novaciano/Magnum-1b_Aesir-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Novaciano/Magnum-1b_Aesir-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use Novaciano/Magnum-1b_Aesir-GGUF with Docker Model Runner:
```
docker model run hf.co/Novaciano/Magnum-1b_Aesir-GGUF
```

Lemonade

How to use Novaciano/Magnum-1b_Aesir-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Novaciano/Magnum-1b_Aesir-GGUF

Run and chat with the model

lemonade run user.Magnum-1b_Aesir-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Magnum-1b_Aesir-GGUF / README.md

Novaciano

Update README.md

1356bfe verified over 1 year ago

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metadata

base_model: UUFO-Aigis/Magnum-1b-v1
tags:
  - llama-cpp
  - koboldcpp
  - nsfw
  - rp
  - roleplay
  - español
  - 1b
  - 4-bit
  - Llama 3.2
  - not-for-all-audiences
license: apache-2.0
datasets:
  - MinervaAI/Aesir-Preview
language:
  - en
  - es

Magnum 1b Aesir

Este es el modelo Magnum 1B de UUFO-Aigis combinado con el dataset Aesir Preview de MinervaAI.

Mejoras conocidas:

Si, fue creado en base de un modelo entrenado con datasets exclusivamente para partidas roleplay.

No se conocen mejoras técnicas.

Lo conforman dos versiones:

IQ4_XS: Es una versión rápida e ideal para celulares pero con un costo minimo de coherencia.
Q5_0: Es una versión mas... digamos... inteligente, pero pide mayor requisitos computacionales.

Elige la versión que más se adapte a tus necesidades.