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
File size: 657 Bytes
2216aae | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | from more_itertools import consume # noqa: F401
# copied from jaraco.itertools 6.1
def ensure_unique(iterable, key=lambda x: x):
"""
Wrap an iterable to raise a ValueError if non-unique values are encountered.
>>> list(ensure_unique('abc'))
['a', 'b', 'c']
>>> consume(ensure_unique('abca'))
Traceback (most recent call last):
...
ValueError: Duplicate element 'a' encountered.
"""
seen = set()
seen_add = seen.add
for element in iterable:
k = key(element)
if k in seen:
raise ValueError(f"Duplicate element {element!r} encountered.")
seen_add(k)
yield element
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