torch2transformer 0.1.0

Wrap plain PyTorch models for the Hugging Face Transformers ecosystem

torch2transformer

torch2transformer lets you wrap plain PyTorch models so they work seamlessly with the Hugging Face Transformers ecosystem. Important note: The original PyTorch model class must be available at run time and load time.

Features

• Use Trainer with any PyTorch model
• Save / load via save_pretrained
• Minimal adapter interface
• No custom training loops

Example

from torch2transformer import TorchAdapter, wrap_model, load_model

# wrap Pytorch model as a Transformer model
model = wrap_model(
    torch_model_cls=TinyCharModel,
    torch_model_kwargs={"vocab_size": 100, "hidden_size": 32},
    task_type="causal_lm"
)
# then can be used with Trainer()

# save model
model.save_pretrained("./tiny_ckpt")

# load model
model = load_model("./tiny_ckpt", torch_model_cls=TinyCharModel)