Remove open pi patch and use custom transformer branch for now

docs/source/libero.mdx

@@ -127,4 +127,44 @@ LeRobot uses MuJoCo for simulation. You need to set the rendering backend before
 
 ## Reproducing π₀ and π₀.₅ results
 
-We can also reproduce the results of π₀ and π₀.₅ on the Libero benchmark by using the finetuned libero models.
+We reproduce the results of π₀ and π₀.₅ on the LIBERO benchmark using the LeRobot implementation. We take the Physical Intelligence LIBERO base models (`pi0_libero` and `pi05_libero`) and finetune them for an additional 6k steps in bfloat16, with batch size of 256 on 8 H100 GPUs using the [HuggingFace LIBERO dataset](https://huggingface.co/datasets/HuggingFaceVLA/libero).
+
+The finetuned models can be found here:
+
+- **π₀ LIBERO**: [pepijn223/pi0_libero_fp32](https://huggingface.co/pepijn223/pi0_libero_fp32)
+- **π₀.₅ LIBERO**: [pepijn223/pi05_libero_fp32](https://huggingface.co/pepijn223/pi05_libero_fp32)
+
+We then evaluate the finetuned models using the LeRobot LIBERO implementation, by running the following command:
+
+```bash
+python src/lerobot/scripts/eval.py \
+  --output_dir=/logs/ \
+  --env.type=libero \
+  --env.task=libero_spatial,libero_object,libero_goal,libero_10 \
+  --eval.batch_size=1 \
+  --eval.n_episodes=5 \
+  --policy.path=pepijn223/pi0_libero_fp32 \
+  --env.multitask_eval=true \
+  --output_dir=./eval_logs/ \
+  --policy.compile_model=false \
+  --policy.gradient_checkpointing=false \
+  --env.max_parallel_tasks=1
+```
+
+**Note:** We set `n_action_steps=10` which normally has a default value of 50.
+
+### Results
+
+We obtain the following results on the LIBERO benchmark:
+
+| Model    | LIBERO Spatial | LIBERO Object | LIBERO Goal | LIBERO 10 | Average |
+| -------- | -------------- | ------------- | ----------- | --------- | ------- |
+| **π₀**   | x              | x             | x           | x         | **x**   |
+| **π₀.₅** | 98.0           | 99.0          | 97.0        | 93.0      | **x**   |
+
+These results are consistent with the original results reported by Physical Intelligence:
+
+| Model    | LIBERO Spatial | LIBERO Object | LIBERO Goal | LIBERO 10 | Average   |
+| -------- | -------------- | ------------- | ----------- | --------- | --------- |
+| **π₀**   | 96.8           | 98.8          | 95.8        | 85.2      | **94.15** |
+| **π₀.₅** | 98.8           | 98.2          | 98.0        | 92.4      | **96.85** |

docs/source/pi0.mdx

@@ -21,44 +21,13 @@ As described by Physical Intelligence, while AI has achieved remarkable success
 
 ## Installation Requirements
 
-⚠️ **Warning**: This policy requires patching the Hugging Face `transformers` library.
-
-### Prerequisites
-
-1. Ensure you have the exact version installed:
+1. Install LeRobot by following our [Installation Guide](./installation).
+2. Install Pi0 dependencies by running:
 
    ```bash
-   pip show transformers
+   pip install -e ".[pi]"
    ```
 
-   It must be version **4.53.2**.
-
-2. Apply the custom patches:
-   ```bash
-   cp -r ./src/lerobot/policies/pi0/transformers_replace/* \
-     $(python -c "import transformers, os; print(os.path.dirname(transformers.__file__))")
-   ```
-
-### What the patches do:
-
-- Support the **AdaRMS optimizer**
-- Correctly control the precision of activations
-- Allow the KV cache to be used without updates
-
-**Important Notes:**
-
-- This permanently modifies your `transformers` installation
-- The changes survive reinstalls unless you explicitly remove the patched files or recreate the environment
-
-### Restoring Clean State
-
-To undo the patches and restore a clean state:
-
-```bash
-pip uninstall transformers
-pip install transformers==4.53.2
-```
-
 ## Training Data and Capabilities
 
 π₀ is trained on the largest robot interaction dataset to date, combining three key data sources:

docs/source/pi05.mdx

@@ -29,22 +29,11 @@ This diverse training mixture creates a "curriculum" that enables generalization
 
 ## Installation Requirements
 
-⚠️ **Warning**: This policy requires patching the Hugging Face `transformers` library.
-
-### Prerequisites
-
-1. Ensure you have the exact version installed:
+1. Install LeRobot by following our [Installation Guide](./installation).
+2. Install Pi0.5 dependencies by running:
 
    ```bash
-   pip show transformers
-   ```
-
-   It must be version **4.53.2**.
-
-2. Apply the custom patches:
-   ```bash
-   cp -r ./src/lerobot/policies/pi05/transformers_replace/* \
-     $(python -c "import transformers, os; print(os.path.dirname(transformers.__file__))")
+   pip install -e ".[pi]"
    ```
 
 ### What the patches do: