kermt-pretrain-scratch SKILL.md skillA
This file is byte-identical to the first copy the registry indexed. Same content hash, so the same checks give both the same grade.
kermt-pretrain-scratch from nvidia-bionemo/bionemo-agent-toolkit is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add nvidia-bionemo/bionemo-agent-toolkit/kermt-pretrain-scratch@git:20260825.0e67a61Pins git:20260825.0e67a61 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- nvidia-bionemo/bionemo-agent-toolkit
- Path
skills/bionemo-agent-toolkit/skills/kermt-pretrain-scratch/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260825.0e67a61, committed Aug 25, 2026
- Size
- 9,207 bytes
- Repository stars
- 503
- License
- a license file GitHub does not identify
Pretrain a fresh KERMT model from scratch on a user-provided corpus. Builds a new vocabulary from the corpus, instantiates the model architecture from defaults, and launches pretrain_ddp.py inside the kermt container (detached for long runs). Unlike kermt-continue-pretrain, no starting checkpoint is loaded — the model is randomly initialized.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# kermt-pretrain-scratch Pretrain a brand-new KERMT model from scratch on a user-provided corpus. Useful when you want to retrain a model on a custom chemistry domain rather than extending one of the released checkpoints. **Significantly more expensive than `kermt-continue-pretrain`** — no warm start, so the loss curves need to descend from scratch over many epochs. ## Hardware requirements Same as `kermt-continue-pretrain`: - **GPUs**: 1–N CUDA-capable. The runner auto-detects via `torch.cuda.device_count()`; `--gpus 0,2` overrides. Single-GPU fallback: `--batch_size 32 --save_interval 500`. Multi-GPU keeps defaults (`--batch_size 256` etc.). Note: `--gpus N` uses **torch.cuda** indexing, which can differ from `nvidia-smi`'s display order on multi-GPU hosts (PCI bus vs. CUDA enumeration). To target a specific physical GPU, set `CUDA_VISIBLE_DEVICES` before invoking, or run `python -c "import torch; print([torch.cuda.get_device_name(i) for i in range(torch.cuda.device_count())])"` to confirm which device you're picking. - **VRAM**: the default `--batch-size 256` is sized for A100-class hardware (80 GB VRAM). On smaller GPUs, downscale to avoid OOM: …
Read the whole file at its exact version.
How to install
mdr add nvidia-bionemo/bionemo-agent-toolkit/kermt-pretrain-scratch@sha256:7727a68bcd84d390The line at the top of this page pins the label git:20260825.0e67a61, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_x53yrujnpwmlqth5)
2 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Aug 25, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (9207 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
nvidia-bionemo/bionemo-agent-toolkit · 503 stars · license a license file GitHub does not identify · pushed 2026-11-05 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_x53yrujnpwmlqth5 GET https://markdownregistry.com/api/v1/resolve?ref=nvidia-bionemo/bionemo-agent-toolkit/kermt-pretrain-scratch GET https://markdownregistry.com/api/v1/blob/7727a68bcd84d390a2d88de87adc6be7ff36caeb9bd9b2474289578b74c6f54d
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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