Files
axolotl/examples/ebft/ebft_opencode.py
Wing Lian c50c4acbf4 EBFT: Matching Features, Not Tokens: Energy-Based Fine-Tuning of Language Models (#3527) [skip ci]
* EBFT wip

* fixes

* more fixeS

* add missing strided module

* ebft fixes for multi-turn

* make ebft work with async

* add example for ebft w qwen3.5

* fix for split thinking and update yaml for lora over linear attention only

* enforce_eager for vllm arg in schema

* fix sync weights

* fix multi-gpu

* handle updated sig for mm

* ddp fixes

* improve multi-gpu handling, don't calculate logits, adaptive completion length

* chore: lint

* chore: lint

* support completion_mean

* Address corereview feedback

* clamp min IS ratio

* Address PR code review

* more fixes identified

* address code review

* Fix property from rebase conflict
2026-03-24 18:43:46 -04:00

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Python

"""
Dataset transform for nvidia/OpenCodeInstruct with EBFT.
Maps the dataset's `input` (prompt) and `output` (code solution) fields
to the format expected by the EBFT trainer.
"""
def transform(cfg, *args, **kwargs):
def transform_fn(example, tokenizer=None):
return {
"prompt": [
{"role": "user", "content": example["input"]},
],
"ground_truth": example["output"],
}
return transform_fn, {
"remove_columns": [
"id",
"domain",
"generation_algorithm",
"llm_judgement",
"unit_tests",
"tests_execution_status",
"average_test_score",
]
}