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nkthebass
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nkthebass
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| Benchmark | This model | Supra2-100M-Instruct |
|---|---|---|
| ARC-Easy | 53.7 | 44.4 |
| ARC-Challenge | 29.0 | 24.7 |
| OpenBookQA | 32.0 | 30.4 |
| PIQA | 65.7 | 64.4 |
| WinoGrande | 50.9 | 50.5 |
| HellaSwag | 33.3 | 35.9 |
| MMLU | 25.7 | 25.8 |
EleutherAI lm-eval-harness v0.4.12, 0-shot, on the HF repo (not the GGUF — llama.cpp's --multiple-choice path under-reports these tasks):
bash
lm_eval --model hf \--model_args pretrained=nkthebass/tinybrainbot-100m-v3-math,dtype=float32 \--tasks hellaswag,arc_easy,arc_challenge,openbookqa,winogrande,piqa,mmlu \--num_fewshot 0 --batch_size 32
Metrics: acc_norm for HellaSwag / ARC / OpenBookQA / PIQA; acc for WinoGrande & MMLU.
What is 12 + 7 * 3? → "First: 7×3=21, then 12+21 = 33." (the base and general instruct both get this wrong.)python
from transformers import AutoModelForCausalLM, AutoTokenizertok = AutoTokenizer.from_pretrained("nkthebass/tinybrainbot-100m-v3-math")model = AutoModelForCausalLM.from_pretrained("nkthebass/tinybrainbot-100m-v3-math")prompt = "<|user|>\nWhat is 12 + 7 * 3?\n<|end|>\n<|assistant|>\n"ids = tok(prompt, return_tensors="pt").input_idsprint(tok.decode(model.generate(ids, max_new_tokens=60)[0][ids.shape[1]:], skip_special_tokens=True))
An F16 GGUF is included (tinybrainbot-100m-v3-math-f16.gguf) for llama.cpp / Ollama / LM Studio, with the add_space_prefix=false + leading-space chat template baked in — order-of-operations works faithfully from the GGUF.
Not safety-tuned.