transformers-bio-nlp SKILL.md skillA

transformers-bio-nlp from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add jaechang-hits/sciagent-skills/transformers-bio-nlp@git:20260428.81ea2d2

Pins git:20260428.81ea2d2 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
jaechang-hits/sciagent-skills
Path
skills/scientific-computing/transformers-bio-nlp/SKILL.md
Versions recorded
2
Latest version
git:20260428.81ea2d2, committed Apr 28, 2026
First version recorded
Feb 18, 2026
Size
19,790 bytes
Repository stars
381
License
a license file GitHub does not identify

HuggingFace Transformers with biomedical LMs (BioBERT, PubMedBERT, BioGPT, BioMedLM) for scientific NLP: NER (genes, diseases, chemicals), relation extraction, QA, text classification, abstract summarization. Covers loading, biomedical tokenization, inference pipelines, fine-tuning. Alternatives: spaCy en_core_sci_lg (rule-based NER), Stanza (biomedical models), NLTK.

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

# Transformers for Biomedical NLP

## Overview

HuggingFace Transformers provides a unified API to load, run, and fine-tune 500+ biomedical language models. The key biomedical models — BioBERT (trained on PubMed abstracts + PMC full text), PubMedBERT (trained from scratch on PubMed), BioGPT (generative, trained on PubMed), and BioMedLM — significantly outperform general-purpose BERT on biomedical NER, relation extraction, and question answering. The `pipeline()` abstraction handles tokenization, inference, and postprocessing in one call. Fine-tuning on task-specific labeled data (e.g., BC5CDR for chemical/disease NER) takes under an hour on a single GPU. The `datasets` library provides direct access to standard biomedical benchmarks.

## When to Use

- Extracting gene names, disease mentions, drug names, or chemical entities from biomedical abstracts (NER)
- Classifying abstracts by topic, sentiment of clinical outcomes, or PICO elements for systematic reviews
- Answering specific questions from biomedical literature using extractive QA (BioASQ format)
- Generating hypotheses or summaries from biomedical text using BioGPT or BioMedLM
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add jaechang-hits/sciagent-skills/transformers-bio-nlp@sha256:df624cae5c1256f5

The line at the top of this page pins the label git:20260428.81ea2d2, 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.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_i3xw674bg6mpkkpa.svg)](https://markdownregistry.com/a/art_i3xw674bg6mpkkpa)

1 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 2 versions of this file, between Feb 18, 2026 and Apr 28, 2026, about one every 69 days.

versioncommittedcommitsizeaudit
git:20260428.81ea2d2 latest2026-04-28 81ea2d2 19,790 BA view · diff
git:20260218.8eeb82b2026-02-18 8eeb82b 19,970 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (19790 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

GitHub

jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_i3xw674bg6mpkkpa
GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/transformers-bio-nlp
GET https://markdownregistry.com/api/v1/blob/df624cae5c1256f5e2b7543b4a206b9d564967bcdc88debd33b76942cbbb60db

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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