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LLM Training
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Fine-Tuning LLMs with Together AI API
together-core-workflow-a
jeremylongshore/claude-code-plugins-plus-skills
286
A comprehensive workflow guide for fine-tuning open-source Large Language Models (LLMs) using the Together AI API. This process covers preparing structured training data (JSONL format), uploading the file, initiating the fine-tuning job, monitoring the training status, and finally deploying the custom model for inference. Ideal for developers needing to customize models for specific enterprise tasks, such as customer support or specialized content generation.
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Fine-Tuning and Deploying LLMs Workflow
together-core-workflow-b
jeremylongshore/claude-code-plugins-plus-skills
200
This workflow guides users through the complete lifecycle of customizing large language models (LLMs). It covers uploading training data, initiating fine-tuning jobs, monitoring training progress, managing model versions, and finally deploying the optimized model to a dedicated, autoscaling inference endpoint using the Together AI API. Ideal for production-level customization.
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Train and Fine-Tune LLMs Using TRL
trl-training
sickn33/antigravity-awesome-skills
316
This skill provides expert capabilities for training and fine-tuning transformer language models using the TRL (Transformers Reinforcement Learning) library. It supports state-of-the-art post-training methods, including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), Group Relative Policy Optimization (GRPO), and Reward Model training. Use this skill to align and customize foundation models for advanced tasks via CLI commands.
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