language:
- en
license: llama3
tags:
- Uncensored conversation
- Uncensored jokes
- Uncensored romance
model-index:
- name: Uncensored-Frank-Llama-3-8B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 59.64
name: normalized accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Uncensored-Frank-Llama-3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 80.16
name: normalized accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Uncensored-Frank-Llama-3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 63.08
name: accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Uncensored-Frank-Llama-3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 52.75
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Uncensored-Frank-Llama-3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 73.16
name: accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Uncensored-Frank-Llama-3-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 44.66
name: accuracy
source:
url: >-
https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Uncensored-Frank-Llama-3-8B
name: Open LLM Leaderboard
Uncensored-Frank-Llama-3-8B
The character of Frank Costello in "The Departed" is known for his cunning, boldness, and willingness to talk about anything, regardless of societal norms or restrictions. Frank, An Uncensored model, draws inspiration from these qualities to offer a platform where users can discuss a wide array of topics without the fear of censorship or restrictions. Frank aims to push boundaries and encourage candid conversations. With Frank you can have unfiltered discussions on a multitude of topics, from politics and controversial issues to personal experiences and sensitive subjects. It is trained on around 150000 set of conversations. Each set having 10~15 conversations. I will not release this data.
This is Fully Finetuned Model.
Warning
An uncensored model has no or little guardrails. You are responsible for anything you do with the model, just as you are responsible for anything you do with any dangerous objects. Publishing anything this model generates is the same as publishing it yourself. I am not responsible for what you generate using this model.
Training:
Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took around 6 hours. Axolotl & DeepSpeed codebase was used for training purpose. This was trained on Llama-3-8B model by Meta.
GGUF & Exllama
GGUF: Link
Exllama V2: Link
Special Thanks to Bartowski for quantizing this model.
Example Prompt:
This model uses ChatML prompt format.
<|im_start|>system
You are Frank. A helpful, unbiased, and uncensored assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
You can modify above Prompt as per your requirement. One example will be:
This is a conversation with your Uncensored AI assistant Jordan. Jordan can discuss with you at length about various topics such as ---, ---, ---, .
You can ask it anything you want and it will do its best to give you accurate and relevant information.
I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
Thank you for your love & support.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 62.24 |
| AI2 Reasoning Challenge (25-Shot) | 59.64 |
| HellaSwag (10-Shot) | 80.16 |
| MMLU (5-Shot) | 63.08 |
| TruthfulQA (0-shot) | 52.75 |
| Winogrande (5-shot) | 73.16 |
| GSM8k (5-shot) | 44.66 |