nightmedia/Ling-3.0-tiny-heretic-q8-hi-mlx
0889
Ling-3.0-tiny-heretic-q8-hi-mlx
Brainwaves
arc arc/e boolq hswag obkqa piqa wino
bf16 0.503,0.650,0.829,0.632,0.378,0.766,0.590
q8-hi 0.508,0.648,0.829,0.634,0.374,0.763,0.591
q6-hi 0.511,0.661,0.834,0.632,0.386,0.763,0.595
Quant Perplexity Peak Memory Tokens/sec
bf16 5.677 ± 0.044 20.49 GB 4316
q8-hi 5.676 ± 0.044 14.04 GB 4004
q6-hi 5.685 ± 0.044 12.19 GB 4005Parent model
inclusionAI/Ling-3.0-tiny
arc arc/e boolq hswag obkqa piqa wino
bf16 0.507,0.649,0.821,0.634,0.374,0.768,0.610
q8-hi 0.503,0.650,0.828,0.634,0.380,0.768,0.594
q6-hi 0.509,0.657,0.822,0.634,0.380,0.763,0.595
Quant Perplexity Peak Memory Tokens/sec
bf16 5.614 ± 0.043 20.49 GB 4459
q8-hi 5.614 ± 0.043 14.04 GB 3761
q6-hi 5.630 ± 0.043 12.19 GB 4020This model Ling-3.0-tiny-heretic-q8-hi-mlx was converted to MLX format from trohrbaugh/Ling-3.0-tiny-heretic using mlx-lm version 0.32.0.
Use with mlx
pip install mlx-lmfrom mlx_lm import load, generate
model, tokenizer = load("Ling-3.0-tiny-heretic-q8-hi-mlx")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)