Instructions to use alpha-ai/OopsHusBot-3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alpha-ai/OopsHusBot-3B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alpha-ai/OopsHusBot-3B-GGUF", dtype="auto") - llama-cpp-python
How to use alpha-ai/OopsHusBot-3B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="alpha-ai/OopsHusBot-3B-GGUF", filename="OopsHusBot-3B.Q4_K_M.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 alpha-ai/OopsHusBot-3B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
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 alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
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 alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use alpha-ai/OopsHusBot-3B-GGUF with Ollama:
ollama run hf.co/alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
- Unsloth Studio new
How to use alpha-ai/OopsHusBot-3B-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 alpha-ai/OopsHusBot-3B-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 alpha-ai/OopsHusBot-3B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for alpha-ai/OopsHusBot-3B-GGUF to start chatting
- Pi new
How to use alpha-ai/OopsHusBot-3B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use alpha-ai/OopsHusBot-3B-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use alpha-ai/OopsHusBot-3B-GGUF with Docker Model Runner:
docker model run hf.co/alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
- Lemonade
How to use alpha-ai/OopsHusBot-3B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull alpha-ai/OopsHusBot-3B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.OopsHusBot-3B-GGUF-Q4_K_M
List all available models
lemonade list
Uploaded Model
- Developed by: Alpha AI
- License: apache-2.0
- Finetuned from model: meta-llama/Llama-3.2-3B-Instruct
This llama model was trained 2x faster with Unsloth and Hugging Face's TRL library.
OopsHusBot-3B: The AI Model for Husbands Who Try (and Sometimes Fail) at Communication
Overview
Husbands mean well. Really. But communication can sometimes feel like an unsolvable puzzle. OopsHusBot-3B is here to help! Designed to assist husbands in navigating tricky conversations, avoiding misunderstandings, and delivering just the right amount of romance (without overdoing it), this model is your ultimate survival guide for relationship communication.
Built on meta-llama/Llama-3.2-3B-Instruct, this model is fine-tuned to prevent classic communication blunders—because sometimes, a simple “OK” isn’t the right answer.
Model Details
- Base Model: meta-llama/Llama-3.2-3B-Instruct
- Fine-tuned By: Alpha AI
- Training Framework: Unsloth
Quantization Levels Available
- q4_k_m
- q5_k_m
- q8_0
- 16-bit (Full precision) - Link
(Note: The INT1 16-bit link is referenced (https://huggingface.co/alphaaico/OopsHusBot-3B)
Format: GGUF (Optimized for local deployments, https://huggingface.co/alphaaico/OopsHusBot-3B-GGUF)
Key Features
- Auto-Smooth Talk – Helps generate heartfelt, thoughtful responses without sounding robotic.
- Oops Recovery Mode – Immediate damage control when you say something unintentionally dumb.
- Danger Phrase Decoder – Correctly interprets high-risk phrases like “Do whatever you want” (Hint: She doesn’t mean that).
- Anniversary & Birthday Reminder – Generates sweet, meaningful texts to keep you in the clear.
- Pre-Apology Generator – Because sometimes, you don’t know what you did wrong—but you know you need to fix it.
- Selective Hearing Fixer – Crafts responses to make it seem like you were totally paying attention.
Training & Data
OopsHusBot-3B has been trained on a carefully curated dataset of:
Romantic yet slightly clueless husband responses
Apology best practices (ranked by effectiveness)
Deciphering “I’m fine” and other cryptic messages
Emergency sweet talk for when things go south
When to text “I love you” without being asked
Avoiding the classic “Are you mad?” trap
Important Warnings
❌ Not responsible for husbands who still say “Calm down.”
❌ Does not fix situations where you actually forgot her birthday.
❌ AI-generated compliments may be too good, causing suspicion.
❌ Disables “I told you so” responses for your safety.
Use Cases
- When she says “I have nothing to wear” – Generates supportive yet non-argumentative responses.
- Emergency Romance Mode – For those “You never say nice things to me” situations.
- Silent Treatment Prevention – Helps craft messages to de-escalate tension before it spirals.
- Reading Between the Lines – Ensures you don’t misinterpret “Do whatever you want.”
- Gift Idea Generator – Ensures you never make the mistake of buying a vacuum as a romantic gift again.
Model Performance
OopsHusBot-3B has been further optimized to deliver:
- Empathic and Context-Aware Responses – Improved understanding of user inputs with a focus on empathetic replies.
- High Efficiency on Consumer Hardware – Maintains quick inference speeds even with more advanced conversation modeling.
- Balanced Coherence and Creativity – Strikes an ideal balance for real-world dialogue applications, allowing for both coherent answers and creative flair.
Limitations & Biases
Like any AI system, this model may exhibit biases stemming from its training data. Users should employ it responsibly and consider additional fine-tuning if needed for sensitive or specialized applications.
License
Released under the Apache-2.0 license. For full details, please consult the license file in the Hugging Face repository.
Acknowledgments
Special thanks to the Unsloth team for their optimized training pipeline for LLaMA models. Additional appreciation goes to Hugging Face’s TRL library for enabling accelerated and efficient fine-tuning workflows.
NOTE - If you’re a husband who means well but sometimes just doesn’t get it—OopsHusBot-3B has your back. 🚀🔥
- Downloads last month
- 15
4-bit
5-bit
8-bit
Model tree for alpha-ai/OopsHusBot-3B-GGUF
Base model
meta-llama/Llama-3.2-3B-Instruct