LLM TRAINING
LLM training: turn your LLM into a specialist editor.
Training can turn a generic LLM into a specialist editor that follows your rules in its thinking processes, reflects your tone of voice and uses the terminology from your field.
LLM training: how to turn an LLM into an invaluable ally
Large Language Models (or LLMs, such as GPT-4, Claude, and Llama) are artificial intelligence systems with the capacity to understand natural language and edit texts, following complex instructions and adapting to specific contexts.
A generic model trained using billions of pages from the internet will produce editing results that are just as generic, failing to use the right terminology for your field, reflect your tone of voice and truly encapsulate your brand’s DNA.
The answer lies in LLM training: it can turn a generic LLM into a specialist editor that follows your rules in its thinking processes. Keep reading to find out how.
How it works: prompt engineering + fine-tuning
LLM training involves a combination of two processes that can produce exceptional results if they are set up properly: prompt engineering and fine-tuning.
PROMPT ENGINEERING
Prompt engineering is the art of giving precise instructions that teach a model how to think in accordance with your brand’s rules, what restrictions apply, which examples to follow and how to handle exceptions. The model learns these “lessons” and consistently puts them into practice every time you ask a question or ask it to complete a task.
FINE-TUNING
During this stage, the model draws directly on your translation memories to learn the language, writing style and terminology of your industry and brand. The system will study the examples until it gains an in-depth understanding of them, so with each iteration it gets more and more precise and comes closer and closer to satisfying your quality requirements.
THE LLM TRAINING OUTCOME
Eventually, you will end up with a “customised multilingual AI editor” that does not just translate automatically but also follows your rules as it does so, giving it the capacity to turn rough drafts into finished texts that meet all of your quality standards in every respect.
HARNESS THE POWER OF AI WITH LLM TRAINING
Expert human editors still have an invaluable part to play. Complex decisions, cultural considerations and editorial choices remain the preserve of human intelligence.
What an LLM can do, thanks to LLM training, is increase the productivity of a human editor by automating repetitive tasks and preserving consistency in standardised procedures, freeing up precious time for really strategic matters and helping businesses to evolve.
Rather than competing, our approach sees people and technology collaborating with each other. And the end result is significantly better than it would be with either of them working alone.
The LLM training process
1. ANALYSIS AND CURATION
We study your tone of voice, copywriting guides, terminological glossaries, and examples of “copy-edited” texts in order to identify the patterns, rules and conventions in your approach to communication.
2. Dataset preparation
We collect and structure pairs of “original” and “copy-edited” texts, each of which will provide input. The greater the quality and variety of the dataset, the better the subsequent training will be.
3. ITERATIVE TRAINING AND VALIDATION
We gradually train the model, with constant validation using separate datasets.
4. QUALITY ASSURANCE BY A SPECIALIST NATIVE SPEAKER
The trained model goes up against generic baseline models during A/B testing, with validation by linguists and editors who check compliance with style guides, terminological consistency, grammatical quality and cultural appropriateness.
5. DEPLOYMENT AND CONTINUOUS IMPROVEMENT
The model is integrated into workflows (APIs, web interfaces, CMS plugins) and a continuous feedback system enables regular improvements.
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