Instructions to use hf-tiny-model-private/tiny-random-FunnelForTokenClassification 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-FunnelForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-FunnelForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-FunnelForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06556093040a7585acc2962e8cc172c3e2edbfe4aca57268f6868a2011de0a59
- Size of remote file:
- 420 kB
- SHA256:
- e4f622705d488de273fbef2028a88b73844d0f6a4426cb07c247c9bbc8a946b2
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