Felprot75/Llama-3.1-8B-Lexi-Uncensored-V2-mlx_4bit
The Model Felprot75/Llama-3.1-8B-Lexi-Uncensored-V2-mlx_4bit was converted to MLX format from Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 using mlx-lm version 0.21.1.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Felprot75/Llama-3.1-8B-Lexi-Uncensored-V2-mlx_4bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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Model tree for Felprot75/Llama-3.1-8B-Lexi-Uncensored-V2-mlx_4bit
Base model
Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard77.920
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard29.690
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard16.920
- acc_norm on GPQA (0-shot)Open LLM Leaderboard4.360
- acc_norm on MuSR (0-shot)Open LLM Leaderboard7.770
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard30.900