liger kernel (#4)

Author: EdoardoMosca

README.md

@@ -60,8 +60,6 @@ When training is done, you can bundle your output checkpoint with `leap-bundle`
 
 ## 🧪 Advanced Configuration
 
-### Default Configs Location and Adding New Configs
-
 The default configurations are located in:
 
 - **SFT Training**: [`src/leap_finetune/configs/sft_configs.py`](./src/leap_finetune/configs/sft_configs.py)
@@ -70,6 +68,9 @@ The default configurations are located in:
 
 To add a new training configuration add it to the respective file and then reference it in [`src/leap_finetune/configs/__init__.py`](./src/leap_finetune/configs/__init__.py) in the `TrainingConfig` and/or `PeftConfig` enum.
 
+We also support [Liger Kernel](https://github.com/linkedin/Liger-Kernel) and it comes pre-installed.
+Just add `"use_liger_kernel": True"` to your `user_config`
+
 ## Contributing
 
 1. Hook `pre-commit` to git: `uv run pre-commit install`

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "leap-finetune"
 version = "0.1.0"
-description = "A simple trl wrapper to streamline v2 fine-tuning"
+description = "A minimal fine-tuning repo for LFM2, fully built on Open Source."
 readme = "README.md"
 authors = [
     { name = "Liquid AI", email = "support@liquid.ai" }
@@ -13,9 +13,10 @@ dependencies = [
     "deepspeed>=0.17.1",
     "ray[train]>=2.47.1",
     "torch>=2.7.1",
-    "transformers",
+    "transformers>=4.55.0",
     "trl>=0.18.2",
     "rich>=14.1.0",
+    "liger-kernel>=0.6.1",
 ]
 
 [project.scripts]
@@ -30,6 +31,3 @@ dev = [
     "pre-commit>=4.2.0",
     "ruff>=0.11.13",
 ]
-
-[tool.uv.sources]
-transformers = { git = "https://github.com/huggingface/transformers.git", rev = "bf607f6d3bd7bf95aaa1094c3a51c3476e4ddc29" }