base_model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
library_name: transformers
license: llama3.1
tags:
- llama-cpp
- gguf-my-repo
model-index:
- name: Llama-3.1-8B-Lexi-Uncensored-V2
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 77.92
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 29.69
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 16.92
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 4.36
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 7.77
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 30.9
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
name: Open LLM Leaderboard
Triangle104/Llama-3.1-8B-Lexi-Uncensored-V2-Q4_K_M-GGUF
This model was converted to GGUF format from Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Model details:
VERSION 2 Update Notes:
More compliant
Smarter
For best response, use this system prompt (feel free to expand upon it as you wish):
Think step by step with a logical reasoning and intellectual sense before you provide any response.
For more uncensored and compliant response, you can expand the system message differently, or simply enter a dot "." as system message.
IMPORTANT: Upon further investigation, the Q4 seems to have refusal issues sometimes. There seems to be some of the fine-tune loss happening due to the quantization. I will look into it for V3. Until then, I suggest you run F16 or Q8 if possible.
image/png GENERAL INFO:
This model is based on Llama-3.1-8b-Instruct, and is governed by META LLAMA 3.1 COMMUNITY LICENSE AGREEMENT
Lexi is uncensored, which makes the model compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones.
You are responsible for any content you create using this model. Please use it responsibly.
Lexi is licensed according to Meta's Llama license. I grant permission for any use, including commercial, that falls within accordance with Meta's Llama-3.1 license. IMPORTANT:
Use the same template as the official Llama 3.1 8B instruct. System tokens must be present during inference, even if you set an empty system message. If you are unsure, just add a short system message as you wish. FEEDBACK:
If you find any issues or have suggestions for improvements, feel free to leave a review and I will look into it for upcoming improvements and next version.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here Metric Value Avg. 27.93 IFEval (0-Shot) 77.92 BBH (3-Shot) 29.69 MATH Lvl 5 (4-Shot) 16.92 GPQA (0-shot) 4.36 MuSR (0-shot) 7.77 MMLU-PRO (5-shot) 30.90
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo Triangle104/Llama-3.1-8B-Lexi-Uncensored-V2-Q4_K_M-GGUF --hf-file llama-3.1-8b-lexi-uncensored-v2-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/Llama-3.1-8B-Lexi-Uncensored-V2-Q4_K_M-GGUF --hf-file llama-3.1-8b-lexi-uncensored-v2-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo Triangle104/Llama-3.1-8B-Lexi-Uncensored-V2-Q4_K_M-GGUF --hf-file llama-3.1-8b-lexi-uncensored-v2-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/Llama-3.1-8B-Lexi-Uncensored-V2-Q4_K_M-GGUF --hf-file llama-3.1-8b-lexi-uncensored-v2-q4_k_m.gguf -c 2048