QuantFactory / Daredevil-8B-abliterated-GGUF

huggingface.co
Total runs: 815
24-hour runs: 0
7-day runs: 196
30-day runs: 492
Model's Last Updated: May 30 2024
text-generation

Introduction of Daredevil-8B-abliterated-GGUF

Model Details of Daredevil-8B-abliterated-GGUF

Daredevil-8B-abliterated-GGUF

This is quantized version of mlabonne/Daredevil-8B-abliterated created using llama.cpp

Model Description

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Abliterated version of mlabonne/Daredevil-8B using failspy 's notebook.

It based on the technique described in the blog post " Refusal in LLMs is mediated by a single direction ".

Thanks to Andy Arditi, Oscar Balcells Obeso, Aaquib111, Wes Gurnee, Neel Nanda, and failspy.

🔎 Applications

This is an uncensored model. You can use it for any application that doesn't require alignment, like role-playing.

Tested on LM Studio using the "Llama 3" preset.

🏆 Evaluation
Open LLM Leaderboard

Daredevil-8B-abliterated is the second best-performing 8B model on the Open LLM Leaderboard in terms of MMLU score (27 May 24).

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Nous

Evaluation performed using LLM AutoEval . See the entire leaderboard here .

Model Average AGIEval GPT4All TruthfulQA Bigbench
mlabonne/Daredevil-8B 📄 55.87 44.13 73.52 59.05 46.77
mlabonne/Daredevil-8B-abliterated 📄 55.06 43.29 73.33 57.47 46.17
mlabonne/Llama-3-8B-Instruct-abliterated-dpomix 📄 52.26 41.6 69.95 54.22 43.26
meta-llama/Meta-Llama-3-8B-Instruct 📄 51.34 41.22 69.86 51.65 42.64
failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 📄 51.21 40.23 69.5 52.44 42.69
mlabonne/OrpoLlama-3-8B 📄 48.63 34.17 70.59 52.39 37.36
meta-llama/Meta-Llama-3-8B 📄 45.42 31.1 69.95 43.91 36.7
🌳 Model family tree

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💻 Usage
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "mlabonne/Daredevil-8B-abliterated"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

Runs of QuantFactory Daredevil-8B-abliterated-GGUF on huggingface.co

815
Total runs
0
24-hour runs
175
3-day runs
196
7-day runs
492
30-day runs

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