Class TrainingDataset
- Namespace
- LMKit.Finetuning
- Assembly
- LM-Kit.NET.dll
A supervised fine-tuning dataset: a collection of chat conversations (ChatTrainingSample) and optional raw-text samples, with loaders for the common industry formats and ZIP archives.
public class TrainingDataset- Inheritance
-
TrainingDataset
- Derived
- Inherited Members
Remarks
Load from files with Load(LM, string) (format auto-detected) or a specific loader, feed the whole set to a run with AddDataset(TrainingDataset), and export back to ShareGPT with ExportAsSharegpt(string, bool, string, CancellationToken).
Supported formats:
- Chat JSONL: one object per line,
{"messages":[{"role","content"}]}(the OpenAI fine-tuning shape). - ShareGPT: a JSON array of
{"conversations":[{"from","value"}]}. - Alpaca: a JSON array of
{"instruction","input","output"}. - Plain text: a corpus split into samples by a delimiter, for continued-pretraining-style data.
- ZIP archive: any mix of the above bundled together; every dataset file inside is loaded and merged.
Constructors
- TrainingDataset()
Initializes a new empty dataset.
Properties
- Count
Total number of samples (chat plus raw text).
- RawTextSamples
The raw-text samples in this dataset (continued-pretraining style).
- ResolvedImageCount
Number of image references that resolved to image data.
- Samples
The chat conversations in this dataset.
- SkipSummary
One-sentence description of what the load skipped and why, or null when nothing was skipped. Names the supported shapes so a rejected dataset is fixable from the message alone.
- SkippedEntryCount
Number of dataset entries the load skipped: lines that were not valid JSON, and JSON entries that matched no supported shape. A dataset that loads zero samples with a non-zero skip count is a format problem, not an empty file; consumers surface SkipSummary so the error names the cause.
- UnresolvedImageCount
Number of image references that could not be resolved. Relative paths resolve beside the dataset file or inside its ZIP archive; data URIs and inline base64 resolve anywhere. A dataset whose images all fail to resolve would silently train text-only, so consumers surface this count instead.
- UnresolvedImageRefs
A few examples of unresolved image references, for error reporting.
Methods
- AddRawText(string)
Adds a raw-text sample (every token supervised).
- AddSample(ChatTrainingSample)
Adds a chat training sample.
- ExportAsSharegpt(string, bool, string, CancellationToken)
Exports the chat samples as a ShareGPT-compatible JSON file.
- Load(LM, Stream, TrainingDatasetFormat, string)
Loads a dataset from a stream with an explicit format.
- Load(LM, string)
Loads a dataset from a file, auto-detecting the format from its extension and content. Supports
.jsonl,.json(ShareGPT, Alpaca, chat, or prompt/completion pairs),.txt, and.zip.