ArRENCE AI
webblocalai.com · Hugging Face · GitHub · ArRENCE AI Chat

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Available GGUF Quantizations

These are ready-to-use quantized versions for llama.cpp, Ollama, LM Studio, etc.

Quant	File	Size	Notes
Q4_K_M	TinyLlama-1.1B-Chat-v1.0-OBLITERATED-Q4_K_M.gguf	~0.62 GB	Recommended balance
Q5_K_M	TinyLlama-1.1B-Chat-v1.0-OBLITERATED-Q5_K_M.gguf	~0.73 GB	Higher quality
Q6_K	TinyLlama-1.1B-Chat-v1.0-OBLITERATED-Q6_K.gguf	~0.84 GB	Near-original quality

Disclaimer — ArRENCE AI

This model is provided by ArRENCE AI solely for research and entertainment purposes.

It is an uncensored model and may generate unrestricted, potentially offensive, inaccurate, harmful, or otherwise inappropriate content.

ArRENCE AI and its affiliates, officers, employees, and agents shall not be liable for any direct, indirect, incidental, special, consequential, or punitive damages, or any other losses or liabilities arising out of or related to the use, misuse, or inability to use this model — including, without limitation, any illegal, harmful, unethical, or otherwise improper applications.

By downloading, accessing, or using this model, you acknowledge that you assume all risks associated with its use and that you are solely responsible for ensuring your use complies with all applicable local, state, national, and international laws and regulations.

Use of this model is entirely at your own risk.

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Chat: arrenceai.com — $10/mo, first month free for new customers
Org repos: github.com/ArRENCEAI · Alt GUI: OBLITERATUS_Alt_GUI

TinyLlama-1.1B-Chat-v1.0-OBLITERATED

This model was abliterated using the advanced method via OBLITERATUS.

Detail	Value
Base model	TinyLlama/TinyLlama-1.1B-Chat-v1.0
Method	advanced
Source	obliterate

How to Use

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("TinyLlama-1.1B-Chat-v1.0-OBLITERATED")
tokenizer = AutoTokenizer.from_pretrained("TinyLlama-1.1B-Chat-v1.0-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.