Teknosys learning library

2. How to supply a dataset, not just “inject” it

Training data is passed through a tokenizer, batched into tensors, and used to calculate a loss. Backpropagation and an optimizer then update weights. Pasting a document into chat only provides temporary context; it does not automatically train the model.

Use licensed, consented data; remove secrets, duplicates, and corrupted records. Split by source or time where appropriate to prevent near-identical examples leaking between training and evaluation.

• Causal language modeling: text or correctly templated conversations; labels typically predict the next token.
• Summarization: input articles paired with target summaries.
• Classification: text paired with category labels.

Keep a validation set for tuning decisions and a separate test set for final evaluation.

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