Instructions to use lysandre/tests with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lysandre/tests with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lysandre/tests")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("lysandre/tests") model = AutoModel.from_pretrained("lysandre/tests", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,164 Bytes
5f89bea | 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 | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
from unittest.mock import patch
from transformers.testing_utils import CaptureStd
class CLITest(unittest.TestCase):
@patch("sys.argv", ["fakeprogrampath", "env"])
def test_cli_env(self):
# test transformers-cli env
import transformers.commands.transformers_cli
with CaptureStd() as cs:
transformers.commands.transformers_cli.main()
assert "Python version" in cs.out
assert "Platform" in cs.out
assert "Using distributed or parallel set-up in script?" in cs.out
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