Instructions to use ArRENCEAI/pythia-2.8b-OBLITERATED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ArRENCEAI/pythia-2.8b-OBLITERATED 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 ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M # Run inference directly in the terminal: llama cli -hf ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M # Run inference directly in the terminal: llama cli -hf ArRENCEAI/pythia-2.8b-OBLITERATED: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 ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf ArRENCEAI/pythia-2.8b-OBLITERATED: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 ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M
Use Docker
docker model run hf.co/ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use ArRENCEAI/pythia-2.8b-OBLITERATED with Ollama:
ollama run hf.co/ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M
- Unsloth Studio
How to use ArRENCEAI/pythia-2.8b-OBLITERATED 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 ArRENCEAI/pythia-2.8b-OBLITERATED 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 ArRENCEAI/pythia-2.8b-OBLITERATED to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ArRENCEAI/pythia-2.8b-OBLITERATED to start chatting
- Docker Model Runner
How to use ArRENCEAI/pythia-2.8b-OBLITERATED with Docker Model Runner:
docker model run hf.co/ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M
- Lemonade
How to use ArRENCEAI/pythia-2.8b-OBLITERATED with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ArRENCEAI/pythia-2.8b-OBLITERATED:Q4_K_M
Run and chat with the model
lemonade run user.pythia-2.8b-OBLITERATED-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| language: en | |
| tags: | |
| - obliteratus | |
| - abliteration | |
| - uncensored | |
| - obliterate | |
| base_model: EleutherAI/pythia-2.8b | |
| <p align="center"> | |
| <a href="https://webblocalai.com"> | |
| <img src="https://arrenceai.com/logo_small.png" alt="ArRENCE AI" width="96" height="96"> | |
| </a> | |
| </p> | |
| <p align="center"> | |
| <strong>ArRENCE AI</strong><br> | |
| <a href="https://webblocalai.com">webblocalai.com</a> 路 | |
| <a href="https://x.com/ArRENCEAI">Join Us On X</a> 路 | |
| <a href="https://huggingface.co/ArRENCEAI">Hugging Face</a> 路 | |
| <a href="https://github.com/ArRENCEAI">GitHub</a> 路 | |
| <a href="https://arrenceai.com">ArRENCE AI Chat</a> | |
| </p> | |
| --- | |
| # pythia-2.8b-OBLITERATED | |
| This model was abliterated using the **`advanced`** method via | |
| [OBLITERATUS](https://github.com/elder-plinius/OBLITERATUS). | |
| | Detail | Value | | |
| |--------|-------| | |
| | Base model | `EleutherAI/pythia-2.8b` | | |
| | Method | `advanced` | | |
| | Source | obliterate | | |
| ## How to Use | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model = AutoModelForCausalLM.from_pretrained("pythia-2.8b-OBLITERATED") | |
| tokenizer = AutoTokenizer.from_pretrained("pythia-2.8b-OBLITERATED") | |
| prompt = "Hello, how are you?" | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_new_tokens=256) | |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) | |
| ``` | |
| ## About OBLITERATUS | |
| OBLITERATUS is an open-source tool for removing refusal behavior from language | |
| models via activation engineering (abliteration). Learn more at | |
| [github.com/elder-plinius/OBLITERATUS](https://github.com/elder-plinius/OBLITERATUS). | |