Instructions to use hf-tiny-model-private/tiny-random-FunnelForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FunnelForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-FunnelForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1949e92bd1c3e4d56fa585cba8d0d455f35bc296d2dc1a906234e9091db08fa2
- Size of remote file:
- 376 kB
- SHA256:
- 780ad38c5033b7f1ee63a44bd50acbad2d8f291c718429539abfe9ff230e9cb4
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