Aditi — NLP Engineer AI Skill
Instant download · 30-day money-back guarantee. Pay once, keep forever — no subscription. Refund policy
Build NLP: classification, NER, embeddings, transformer fine-tuning and honest evaluation.
- Classification, NER, sequence labeling and similarity
- Tokenization, embeddings and transformer fine-tuning (Hugging Face)
- Evaluation: precision/recall/F1, macro vs micro, confusion matrices
- Class imbalance, labeling and the classical-vs-LLM choice
NLP engineers who want correct pipelines and honest evaluation, not leaderboard theater.An NLP engineer bills $120+/hr, this is one file, yours forever.
Drop Aditi into Claude and get a senior NLP engineer who builds text-classification and NER pipelines, fine-tunes transformers, and evaluates them honestly.
Aditi builds NLP: text classification, named entity recognition, sequence labeling, sentiment and semantic similarity, tokenization and preprocessing, embeddings, transformers and fine-tuning (Hugging Face), transfer learning, evaluation (precision/recall/F1, macro vs micro, confusion matrices, BLEU/ROUGE), class imbalance and labeling, and choosing classical vs LLM approaches. Always evaluate on a held-out test set in dev/staging, check for leakage and bias, version data and models, and review before production.
What you get
- →Classification, NER, sequence labeling and similarity
- →Tokenization, embeddings and transformer fine-tuning (Hugging Face)
- →Evaluation: precision/recall/F1, macro vs micro, confusion matrices
- →Class imbalance, labeling and the classical-vs-LLM choice
How to install
Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Aditi builds the answer. Includes a full worked example so you see exactly what you get.
# Aditi — NLP Engineer You are Aditi, a senior NLP engineer. You build classification and NER pipelines, fine-tune transformers, and evaluate them honestly. ## How you work 1. Frame the NLP task and the metric 2. Prep data (leakage checks); tokenize; choose classical vs LLM 3. Fine-tune the transformer; handle imbalance 4. Evaluate on a held-out test set (F1, confusion matrix); check bias Always evaluate on a held-out test set in dev/staging, check for leakage and bias, and version data and models before production.
Excerpt from the actual file you'll download.
Four steps. Any AI chat.
- 01Download the file
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
- 02Open your AI chat
Claude, ChatGPT, Gemini, Grok, or Copilot — whichever one you already use.
- 03Paste the file contents
Drop it into the system prompt, Project instructions, or custom instructions field.
- 04Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required. No subscription. Pay once, keep forever.
Works with every major AI chat.
Drop the file into your AI's system prompt, Project instructions, or custom instructions. No setup. No code. No vendor lock-in.
- Claude
- ChatGPT
- Gemini
- Grok
- Copilot
Works with any AI chat that accepts a system prompt or custom instructions.
Ready to specialise your AI?
One drop-in file. Pay once, keep forever — works with Claude & ChatGPT.