Hugging Face Transformers Usage
davila7/claude-code-templates
Loads pre-trained Hugging Face Transformers models for text, vision and audio tasks, runs inference with pipelines and fine-tunes on custom datasets.
Best practices for language model pretraining and fine-tuning.
Install NLP Pretraining
$ npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aiming-lab/AutoResearchClaw nlp-pretraining --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/researchclaw/skills/builtin/domain/nlp-pretraining .claude/skills/nlp-pretraining && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "nlp-pretraining" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/nlp-pretraining into .claude/skills/nlp-pretraining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nlp-pretraining", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/nlp-pretrainingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aiming-lab/AutoResearchClaw nlp-pretraining --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/researchclaw/skills/builtin/domain/nlp-pretraining .agents/skills/nlp-pretraining && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nlp-pretraining" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/nlp-pretraining into .agents/skills/nlp-pretraining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nlp-pretraining", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aiming-lab/AutoResearchClaw nlp-pretraining --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/researchclaw/skills/builtin/domain/nlp-pretraining .cursor/skills/nlp-pretraining && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "nlp-pretraining" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/nlp-pretraining into .cursor/skills/nlp-pretraining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nlp-pretraining", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aiming-lab/AutoResearchClaw.git --path researchclaw/skills/builtin/domain/nlp-pretraining--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aiming-lab/AutoResearchClaw nlp-pretraining --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/researchclaw/skills/builtin/domain/nlp-pretraining .gemini/skills/nlp-pretraining && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "nlp-pretraining" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/nlp-pretraining into .gemini/skills/nlp-pretraining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nlp-pretraining", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aiming-lab/AutoResearchClaw nlp-pretrainingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/researchclaw/skills/builtin/domain/nlp-pretraining .github/skills/nlp-pretraining && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "nlp-pretraining" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/nlp-pretraining into .github/skills/nlp-pretraining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nlp-pretraining", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aiming-lab/AutoResearchClaw nlp-pretraining --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/researchclaw/skills/builtin/domain/nlp-pretraining .opencode/skills/nlp-pretraining && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "nlp-pretraining" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/domain/nlp-pretraining into .opencode/skills/nlp-pretraining/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nlp-pretraining", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
nlp-pretraining- GitHub stars
- 15k
- Token cost
- ~280 tokens
- SKILL.md length
- 81 words
- Files
- 1
- Skills in repo
- 34
- Repo updated
- First seen
- Licence
- MIT
At a glance
Best practices for language model pretraining and fine-tuning.
- Reviewing NLP training code
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Tasks that involve Natural language processing
- Tasks that involve Fine-tuning
What it does
NLP Pretraining is an agent skill from aiming-lab/AutoResearchClaw. Best practices for language model pretraining and fine-tuning. Use when generating or reviewing NLP training code.
Its SKILL.md is about 280 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Natural language processing and Fine-tuning. The repository describes itself as: Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. 🦞. The licence is MIT.
When your agent uses it
- Reviewing NLP training code
- Tasks that involve Natural language processing
- Tasks that involve Fine-tuning
Example prompts
- “/nlp-pretraining”
What it can do on your machine
Read from SKILL.md and the folder at commit be4ba47. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
NLP Pretraining loads about 280 tokens when it runs. Until then it costs about 33 tokens; SKILL.md has 81 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from aiming-lab/AutoResearchClaw at commit be4ba47, republished under its MIT licence (© aiming-lab). 81 words, ~280 tokens.
Download SKILL.mdSave it as
.claude/skills/nlp-pretraining/SKILL.md (or your agent's skills folder).- name
- nlp-pretraining
- description
- Best practices for language model pretraining and fine-tuning. Use when generating or reviewing NLP training code.
- metadata.category
- domain
- metadata.trigger-keywords
- language model,pretraining,fine-tuning,bert,gpt,llm,transformer,nlp,text
- metadata.applicable-stages
- 9,10
- metadata.priority
- 3
- metadata.version
- 1.0
- metadata.author
- researchclaw
- metadata.references
- Devlin et al., BERT, NAACL 2019; Hu et al., LoRA, ICLR 2022
NLP Pretraining/Fine-tuning Best Practice
Fine-tuning recipe:
- Use pre-trained checkpoints (HuggingFace hub)
- AdamW optimizer, lr=2e-5 to 5e-5
- Linear warmup (6% of total steps) + linear decay
- Batch size: 16-32 (use gradient accumulation for larger effective batch)
- 3-5 epochs for classification, 1-2 for generation
- Weight decay: 0.01
Parameter-efficient methods:
- LoRA: r=8-64, alpha=16-128, apply to q/v projections
- Prefix tuning: 10-20 prefix tokens
- Adapters: bottleneck dimension 64-256
Evaluation:
- Classification: accuracy, F1 (macro for imbalanced)
- Generation: perplexity, BLEU/ROUGE, human evaluation
- Use multiple seeds and report mean +/- std
© aiming-lab, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in researchclaw/skills/builtin/domain/nlp-pretraining of aiming-lab/AutoResearchClaw.
Open the folder on GitHubat commit be4ba47
Compare with similar skills
NLP Pretraining next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| NLP Pretraining this skillaiming-lab/AutoResearchClaw | 15k | — | ~280 | Automated safety check: Pass | MIT | |
| Hugging Face Transformers Usagedavila7/claude-code-templates | 32k | 12 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Running Zeroshot Nermaziyarpanahi/openmed | 5.5k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Transformersynulihao/AgentSkillOS | 617 | — | ~2.9k | Automated safety check: Pass | None | |
| AI ML Skillswentorai/research-plugins | 298 | 1 repos | ~993 | Automated safety check: Pass | MIT | |
| TransformersK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~2.8k | Automated safety check: Notes | Apache-2.0 |
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Related
Categories
Questions about NLP Pretraining
What does NLP Pretraining do?
Best practices for language model pretraining and fine-tuning. NLP Pretraining is an agent skill from aiming-lab/AutoResearchClaw. Best practices for language model pretraining and fine-tuning.
When should I use NLP Pretraining?
NLP Pretraining fits situations like: reviewing NLP training code; tasks that involve Natural language processing; tasks that involve Fine-tuning.
How do I install NLP Pretraining in Claude Code?
Run `npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a claude-code`. Or copy the skill folder (researchclaw/skills/builtin/domain/nlp-pretraining in aiming-lab/AutoResearchClaw) into .claude/skills/nlp-pretraining in your project. Claude Code loads it when a task matches its description.
How do I install NLP Pretraining in Codex?
Run `npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a codex`. Or copy the skill folder (researchclaw/skills/builtin/domain/nlp-pretraining in aiming-lab/AutoResearchClaw) into .agents/skills/nlp-pretraining in your project. Codex loads it when a task matches its description.
Can I use NLP Pretraining in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aiming-lab/AutoResearchClaw --skill nlp-pretraining -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nlp-pretraining, .gemini/skills/nlp-pretraining, .github/skills/nlp-pretraining and .opencode/skills/nlp-pretraining in your project.
What does NLP Pretraining need to run?
SKILL.md names no scripts, command-line tools or credentials: NLP Pretraining is instructions for the agent only.
Does NLP Pretraining access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is NLP Pretraining safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does NLP Pretraining use?
NLP Pretraining is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does NLP Pretraining use?
About 280 tokens (SKILL.md is roughly 1.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to NLP Pretraining?
Skills that share tags, products or a category with NLP Pretraining: Hugging Face Transformers Usage (davila7/claude-code-templates, 32k stars), Running Zeroshot Ner (maziyarpanahi/openmed, 5.5k stars), Transformers (ynulihao/AgentSkillOS, 617 stars) and AI ML Skills (wentorai/research-plugins, 298 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains NLP Pretraining?
aiming-lab (a GitHub organization) maintains it in aiming-lab/AutoResearchClaw, which has 14,595 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on August 19, 2026.
Source: aiming-lab/AutoResearchClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.