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diffuse-coordinator finetune
Fine-tune a model on a file, in one command.
Imports the corpus, chooses hyperparameters from its size and the machine, and starts the run. Does not serve the result: the command for that is printed when it finishes.
Synopsis
diffuse-coordinator finetune <MODEL> <FILE> [OPTIONS]Arguments
| argument | required | description |
|---|---|---|
MODEL | yes | The model to adapt, as shown by model list |
FILE | yes | The corpus: one JSON object per line, each with a messages array |
Options
| flag | value | default | description |
|---|---|---|---|
--config | <CONFIG> | $DIFFUSE_COORDINATOR_CONFIG | Configuration file. Its [admin] section says where to connect |
--endpoint | <ENDPOINT> | $DIFFUSE_COORDINATOR_ENDPOINT | Coordinator endpoint, e.g. https://coordinator.internal:7443 |
--ca-cert | <CA_CERT> | $DIFFUSE_CA_CERT | The deployment CA certificate (PEM) |
--cert | <CERT> | $DIFFUSE_CERT | This process's certificate chain (PEM) |
--key | <KEY> | $DIFFUSE_KEY | This process's private key (PEM) |
--classification | <CLASSIFICATION> | internal | What this data is, in your organisation's own words |
--as-dataset | <DATASET_KEY> | - | Import the corpus under this name rather than the file's own |
--as | <ADAPTER_KEY> | - | What to call the adapter. Derived from the model and the corpus by default |
--pool | <POOL> | - | Which pool to place it in. Every healthy node by default |
--rank | <RANK> | - | LoRA rank. Higher learns more and costs more |
--alpha | <ALPHA> | - | LoRA alpha; the merged delta is scaled by alpha/rank. Twice the rank by default |
--targets | <TARGETS> | - | Which projections to adapt, comma separated |
--epochs | <EPOCHS> | - | Passes over the corpus. Chosen from its size by default |
--learning-rate | <LEARNING_RATE> | - | Step size |
--batch | <BATCH> | - | Examples per step |
--max-seq-len | <MAX_SEQ_LEN> | - | Tokens per example. Taken from the longest row by default |
Notes
The one-command path: it imports the corpus, chooses hyperparameters from its size and from the machine, and starts the run. It does not serve the result: model serve <base>+<adapter> does that, once you have looked at the losses.
Examples
bash
$ diffuse-coordinator finetune qwen2.5-3b berichte.jsonlimported 2 412 examples
rank 16, lr 1e-4, 3 epochs, batch 4, chosen from the corpus and rechner-01
job 4f2a9c started
Watch it: diffuse-coordinator job watch 4f2a9c