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:
- f780a2f9ec40c730274ee777b737155a3f839b850e9629dbd28acd9f9bf9c989
- Size of remote file:
- 304 kB
- SHA256:
- 689ec3568b8b4528723b2f54a695530872c339c895cffaf7cb3e8cb4f28551fa
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