Instructions to use hf-internal-testing/tiny-random-FunnelForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FunnelForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-FunnelForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FunnelForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-FunnelForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 740aaeb9ae9a4fca64eae6585d9040e41877f00db540711ba9bdd54846f8da64
- Size of remote file:
- 376 kB
- SHA256:
- f57a3158786919e5b4fcf59dbc98b1639dac03aa27c73f9ae6a930d3afa1155c
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