0xBreath/Meta-Llama-3.1-8B-Instruct-abliterated-q8-mlx
The Model 0xBreath/Meta-Llama-3.1-8B-Instruct-abliterated-q8-mlx was converted to MLX format from mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated using mlx-lm version 0.19.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("0xBreath/Meta-Llama-3.1-8B-Instruct-abliterated-q8-mlx")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
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Model tree for 0xBreath/Meta-Llama-3.1-8B-Instruct-abliterated-q8-mlx
Base model
meta-llama/Llama-3.1-8B
Finetuned
meta-llama/Llama-3.1-8B-Instruct
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard73.290
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard27.130
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard6.420
- acc_norm on GPQA (0-shot)Open LLM Leaderboard0.890
- acc_norm on MuSR (0-shot)Open LLM Leaderboard3.210
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard27.810