Instructions to use AlexWortega/moe100m-physics-tinybpe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexWortega/moe100m-physics-tinybpe with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlexWortega/moe100m-physics-tinybpe", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| """Shared serialization for the tiny-vocab physics MoE. | |
| Reuses physics_core.fmt_header / fmt_frame, but reduces every frame's | |
| free-text description to a tiny controlled keyword set so the learned vocab | |
| stays simulation-only. | |
| Controlled description set (after the `Frame N:` token): | |
| - "at rest" <- "All objects are at rest." | |
| - "in motion" <- "All objects are in motion." | |
| - "settling" <- "K of N objects are moving." (partial motion) | |
| Anything else -> dropped (description omitted; frame still emitted). | |
| """ | |
| from __future__ import annotations | |
| import re | |
| import physics_core as pc | |
| _AT_REST = re.compile(r"all objects are at rest", re.I) | |
| _IN_MOTION = re.compile(r"all objects are in motion", re.I) | |
| _PARTIAL = re.compile(r"\d+\s+of\s+\d+\s+objects are moving", re.I) | |
| def reduce_desc(raw: str) -> str: | |
| """Map a frame's free-text description to a controlled keyword (or '').""" | |
| if _AT_REST.search(raw): | |
| return "at rest" | |
| if _IN_MOTION.search(raw): | |
| return "in motion" | |
| if _PARTIAL.search(raw): | |
| return "settling" | |
| return "" | |
| def fmt_frame_reduced(fr: dict) -> str: | |
| """Like pc.fmt_frame but with the description replaced by a keyword.""" | |
| fr2 = dict(fr) | |
| fr2["description"] = reduce_desc(fr.get("description", "")) | |
| return pc.fmt_frame(fr2) | |
| def fmt_header_reduced(header: dict) -> str: | |
| """pc.fmt_header with the free-text Scene description blanked out. | |
| Keeps every structural line (Gravity / Timestep / Type / Difficulty / | |
| Static / Constraints) so the categorical `Type:` token survives, but the | |
| `Scene:` line carries no English prose -> vocab stays sim-only. | |
| """ | |
| h2 = dict(header) | |
| h2["description"] = "" | |
| return pc.fmt_header(h2) | |
| def serialize_scene(header: dict, frames: list) -> str: | |
| """Full scene text: reduced header + reduced frames (no trailing BOS/EOS).""" | |
| txt = fmt_header_reduced(header) | |
| txt += "".join(fmt_frame_reduced(fr) for fr in frames) | |
| return txt | |