Instructions to use hf-internal-testing/tiny-random-FunnelForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FunnelForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-FunnelForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FunnelForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-FunnelForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb682f0396d6e5bad135c2db37dfaa4dd5671849cb2ab6a20152d959c99580ca
- Size of remote file:
- 420 kB
- SHA256:
- 3bc800d37ca8de51b5f04987681b38242237302ea01ccb3f839cb625c7c5aa0b
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