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| This model | FP16 baseline | |
|---|---|---|
| Decode tok/s (avg, long traces) | 1157.12 | 1270.13 |
| Peak memory (GB) | 0.154 | 0.223 |
| Disk size (MB) | 55 | 201 |
| Benchmark | This model | FP16 baseline | n |
|---|---|---|---|
| IFEval (instruction following) | 13.6% | 15.9% | 44 |
| Alpaca-cleaned (instruct F1 vs reference) | 37.5 | 36.2 | 50 |
| Context length | Decode tok/s |
|---|---|
| ~128 tokens | 1202.7 |
| ~256 tokens | 1139.3 |
| ~512 tokens | 1129.9 |
| ~1024 tokens | 1156.6 |
pip install mlx-lm1from mlx_lm import load, generate
2
3model, tokenizer = load("sahilchachra/supra-50m-instruct-8bit-mlx")
4response = generate(model, tokenizer, prompt="Your prompt here", max_tokens=256, verbose=True)| Model | Variant |
|---|---|
| sahilchachra/supra-50m-instruct-8bit-mlx | Affine int8 ← this model |
| sahilchachra/supra-50m-instruct-optiq-5bpw-mlx | OptiQ mixed-precision (target 5.0 bpw) |