Instructions to use toto10/Ooga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toto10/Ooga with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("toto10/Ooga", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,072 Bytes
6434f59 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | # Copyright (c) Facebook, Inc. and its affiliates.
# import cloudpickle
class PicklableWrapper(object):
"""
Wrap an object to make it more picklable, note that it uses
heavy weight serialization libraries that are slower than pickle.
It's best to use it only on closures (which are usually not picklable).
This is a simplified version of
https://github.com/joblib/joblib/blob/master/joblib/externals/loky/cloudpickle_wrapper.py
"""
def __init__(self, obj):
while isinstance(obj, PicklableWrapper):
# Wrapping an object twice is no-op
obj = obj._obj
self._obj = obj
# def __reduce__(self):
# s = cloudpickle.dumps(self._obj)
# return cloudpickle.loads, (s,)
def __call__(self, *args, **kwargs):
return self._obj(*args, **kwargs)
def __getattr__(self, attr):
# Ensure that the wrapped object can be used seamlessly as the previous object.
if attr not in ["_obj"]:
return getattr(self._obj, attr)
return getattr(self, attr)
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