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

from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("helper2424/resnet10-imagenet-1k")