Automate end-to-end LLM fine-tuning workflows with the Tinker API.
npx skills add https://github.com/thejaminator/latteries --skill tinker-thejaminator
Please help me install this Agent Skill. Skill: tinker Source: https://github.com/thejaminator/latteries/tree/main/.claude/skills/tinker Command: npx skills add https://github.com/thejaminator/latteries --skill tinker-thejaminator
Fine-tuning and customizing large language models can be complex and time-consuming; Tinker provides a unified API and cookbook patterns to streamline supervised fine-tuning, reinforcement learning, LoRA training, and multi-modal workflows.
Run a sample training workflow with the Tinker API to fine-tune a base model using LoRA and cookbook patterns.
High-intent search queries and answers about installing and using this skill.
LLM fine-tuning with LoRA is automated using high-level cookbook patterns that create training clients, build data pipelines, and manage training state for reproducible training loops. Low-level API access enables fine-grained optimizer control.
Reinforcement learning for LLMs is handled through the Tinker API, supporting forward and backward passes, sampling workflows, and training state management. Cookbook patterns provide rapid experimentation for RL training loops.
Yes, vision-language modeling is fully supported through flexible data pipelines and model selection. The Tinker API allows you to run multi-modal workflows alongside supervised fine-tuning, RL, and LoRA training.
Yes, low-level API access provides fine-grained control over forward and backward passes, optimizers, and sampling workflows. This complements high-level cookbook patterns for rapid experimentation and reproducible training loops.
You need to create a training client and build a flexible data pipeline for your model selection. The API automates the end-to-end supervised fine-tuning workflow, managing training state and running forward and backward passes.
thinking-machines-labOrchestrates an RLHF workflow with SFT, RM training, and RL via the Tinker API.
automatedigitalFine-tune large language models with LoRA and QLoRA optimization.
issdandavisMerge and validate SFT training data sources for publishing.
HomericIntelligenceExecute model training pipelines with forward and backward passes, gradient updates, and checkpoint management.
