How to use from
llama.cppInstall 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:# Run inference directly in the terminal:
llama cli -hf ArRENCEAI/pythia-2.8b-OBLITERATED:Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf ArRENCEAI/pythia-2.8b-OBLITERATED:# Run inference directly in the terminal:
./build/bin/llama cli -hf ArRENCEAI/pythia-2.8b-OBLITERATED:Use Docker
docker model run hf.co/ArRENCEAI/pythia-2.8b-OBLITERATED:Quick Links
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pythia-2.8b-OBLITERATED
This model was abliterated using the advanced method via
OBLITERATUS.
| Detail | Value |
|---|---|
| Base model | EleutherAI/pythia-2.8b |
| Method | advanced |
| Source | obliterate |
How to Use
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.
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Base model
EleutherAI/pythia-2.8b
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf ArRENCEAI/pythia-2.8b-OBLITERATED:# Run inference directly in the terminal: llama cli -hf ArRENCEAI/pythia-2.8b-OBLITERATED: