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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32d2f686b791385b9df0e0466d34148d1ba15ec0be46a29386769702d85555d4
- Size of remote file:
- 286 kB
- SHA256:
- f20a3abfd44f19338f352baee5cf3f370a28921165db6b1a10bb8256381953aa
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