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

examples/ebft/ebft_opencode.py

@@ -0,0 +1,28 @@
+"""
+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",
+        ]
+    }