Instructions to use jonl521/modeling_simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonl521/modeling_simple with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jonl521/modeling_simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- _C
- _C_flatbuffer
- __pycache__
- _awaits
- _custom_op
- _decomp
- _dispatch
- _dynamo
- _export
- _functorch
- _higher_order_ops
- _inductor
- _lazy
- _library
- _logging
- _numpy
- _prims
- _prims_common
- _refs
- _strobelight
- _subclasses
- _vendor
- accelerator
- amp
- ao
- autograd
- backends
- bin
- compiler
- contrib
- cpu
- csrc
- cuda
- distributed
- distributions
- export
- fft
- func
- futures
- fx
- include
- jit
- lib
- linalg
- masked
- monitor
- mps
- mtia
- multiprocessing
- nested