metadata
license: llama3
tags:
- uncensored
- llama3
- instruct
- open
- llama-cpp
- gguf-my-repo
base_model: Orenguteng/Llama-3-8B-Lexi-Uncensored
model-index:
- name: Llama-3-8B-Lexi-Uncensored
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: 59.56
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Orenguteng/Llama-3-8B-Lexi-Uncensored
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: 77.88
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Orenguteng/Llama-3-8B-Lexi-Uncensored
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: 67.68
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Orenguteng/Llama-3-8B-Lexi-Uncensored
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: 47.72
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Orenguteng/Llama-3-8B-Lexi-Uncensored
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: 75.85
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Orenguteng/Llama-3-8B-Lexi-Uncensored
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: 68.39
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Orenguteng/Llama-3-8B-Lexi-Uncensored
name: Open LLM Leaderboard
Ayyystin/Llama-3-8B-Lexi-Uncensored-Q4_0-GGUF
This model was converted to GGUF format from Orenguteng/Llama-3-8B-Lexi-Uncensored using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
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 --hf-repo Ayyystin/Llama-3-8B-Lexi-Uncensored-Q4_0-GGUF --hf-file llama-3-8b-lexi-uncensored-q4_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Ayyystin/Llama-3-8B-Lexi-Uncensored-Q4_0-GGUF --hf-file llama-3-8b-lexi-uncensored-q4_0.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.
./main --hf-repo Ayyystin/Llama-3-8B-Lexi-Uncensored-Q4_0-GGUF --hf-file llama-3-8b-lexi-uncensored-q4_0.gguf -p "The meaning to life and the universe is"
or
./server --hf-repo Ayyystin/Llama-3-8B-Lexi-Uncensored-Q4_0-GGUF --hf-file llama-3-8b-lexi-uncensored-q4_0.gguf -c 2048