Plugins
6 pluginscurated
Fine-Tune Transformer Model
Fine-tune transformer language models using TRL with support for SFT, DPO, GRPO, and reward model training.
8 skills · plugin
curated
Write Release Notes
Transform git commits into polished, user-facing release notes organized by category.
8 skills · plugin
curated
Fine-Tune HF Model
Select, train, and upload a fine-tuned transformer model using Hugging Face tools.
5 skills · plugin
curated
Create Release Notes and Changelog
Transform git commits and tickets into user-facing release notes and a categorized changelog.
8 skills · plugin
curated
PRD to Implementation Plan
Transform a raw product idea into a structured PRD and then into a technical implementation plan with issues.
11 skills · plugin
curated
Product Idea Validation
Install this pack to transform a raw product idea into clarifying questions, deep research, a PRD, and a phased execution plan with kill criteria.
6 skills · plugin
Results for “transform”
6 skillstransformers
Load pre-trained models from Hugging Face Hub, run pipeline inference, generate text, and fine-tune models on NLP, vision, audio, and multimodal tasks using the Transformers library.
30.2k · bundle
sentence-transformers
Generate high-quality sentence and text embeddings for semantic similarity, clustering, and retrieval using 5000+ pre-trained models. Supports multilingual and domain-specific embeddings for RAG and semantic search.
10.4k · bundle
ouyang
Builds a local RAG memory system that indexes session logs and notes into ChromaDB for semantic recall across agent restarts.
1 · bundle
More results
qdrant-vector-search
Builds production RAG and semantic search systems with Qdrant, covering collection setup, vector indexing, filtered and hybrid search, and integration with LangChain and LlamaIndex.
2
qdrant-vector-search
Build production RAG and semantic search systems with a high-performance vector database written in Rust, supporting hybrid search, filtering, and horizontal scaling.
10.4k · bundle
blip-2-vision-language
Generate image captions, answer visual questions, and perform image-text retrieval using BLIP-2's Q-Former architecture with frozen vision encoders and LLMs.
10.4k · bundle