| language: en | |
| license: apache-2.0 | |
| tags: | |
| - pytorch | |
| - jax-conversion | |
| - transformers | |
| - resnet | |
| - hil-serl | |
| - Lerobot | |
| - vision | |
| - image-classification | |
| library_name: pytorch | |
| # JAX to PyTorch Converted Model (ResNet-10) | |
| It's done in context of porting `HIL-SERL` paper code (https://hil-serl.github.io/) to `Lerobot` (https://github.com/Lerobot/lerobot). | |
| The HF doesn't have ResNet-10 model, which could be pretty usefult for robotics tasks because of it's small size. | |
| This model is converted from JAX to PyTorch, and the weights are preserved. | |
| ## Model Description | |
| [Brief description of the original model and its purpose] | |
| This model is a PyTorch port of the original JAX implementation. The conversion maintains | |
| the original model's architecture and weights while making it accessible to PyTorch users. | |
| The original model is from https://github.com/rail-berkeley/hil-serl/blob/7d17d13560d85abffbd45facec17c4f9189c29c0/serl_launcher/serl_launcher/utils/train_utils.py#L103. | |
| ## Model Details | |
| - **Original Framework:** JAX | |
| - **Target Framework:** PyTorch | |
| - **Model Architecture:** [Specify architecture] | |
| - **Original Model:** [Link to original model] | |
| - **Parameters:** [Number of parameters] | |
| ## Conversion Process | |
| This model was converted using an automated JAX to PyTorch conversion pipeline, ensuring: | |
| - Weight preservation | |
| - Architecture matching | |
| - Numerical stability | |
| ## Usage | |
| ```python | |
| from transformers import AutoModel, AutoTokenizer | |
| model = AutoModel.from_pretrained("lilkm/resnet10_without_pooling") | |
| ``` | |