Instructions to use AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit", dtype="auto")

llama-cpp-python

How to use AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit",
	filename="unsloth.F16.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16
# Run inference directly in the terminal:
llama-cli -hf AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16
# Run inference directly in the terminal:
llama-cli -hf AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit: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 AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16
# Run inference directly in the terminal:
./llama-cli -hf AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit: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 AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16

Use Docker

docker model run hf.co/AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16

LM Studio
Jan
Ollama
How to use AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit with Ollama:
```
ollama run hf.co/AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16
```

Unsloth Studio

How to use AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit 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 AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit 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 AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit to start chatting

Docker Model Runner
How to use AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit with Docker Model Runner:
```
docker model run hf.co/AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16
```

Lemonade

How to use AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit:F16

Run and chat with the model

lemonade run user.Stoicism1_Phi3.5-mini-instruct-GGUF-16bit-F16

List all available models

lemonade list

Stoicism Language Model 1 StLM (Marcus Aurelius, Seneca, Epictetus) - GGUF 16bit

This language model has been fine-tuned with a specialized dataset based on the teachings of Stoic philosophers, including Marcus Aurelius, Seneca, and Epictetus. It captures the essence of Stoic philosophy, offering thoughtful, reflective responses grounded in Stoic principles and keeping the Stoic language and style. Ideal for anyone interested in Stoic wisdom, personal growth, and philosophical discussions, the model can assist in navigating life's challenges with resilience, virtue, and reason.

The model is trained to deliver answers rooted in Stoic thought, providing practical guidance on topics such as emotional control, mindfulness, perseverance, and the pursuit of wisdom. It is well-suited for applications that aim to integrate ancient philosophical insights into modern-day problem-solving, whether through virtual Stoic coaches, AI-powered personal growth tools, or interactive philosophical discussions.

This fine-tuned model is perfect for users seeking advice on managing stress, building mental resilience, and developing a mindset focused on self-control, rationality, and virtue, as advocated by the Stoic philosophers. Whether for meditation, journaling, or day-to-day decision-making, the model brings timeless wisdom to help users lead a more mindful and fulfilling life.

Developed by: AlbertoB12
Finetuned from model : unsloth/phi-3.5-mini-instruct-bnb-4bit

Downloads last month: 39

GGUF

Model size

4B params

Architecture

llama

Hardware compatibility

16-bit

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Collection including AlbertoB12/Stoicism1_Phi3.5-mini-instruct-GGUF-16bit

Stoicism

Collection

A collection of Stoicism models and datasets, ideal for AI training, philosophical applications, and personal growth tools. • 11 items • Updated Mar 2