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:
- bb7d530f89fb50970e1e6b9eda5be300377deedb53a0d515edd31482bf92994b
- Size of remote file:
- 337 kB
- SHA256:
- 16f025e9db1dfbd0d8c31e674e70f4d7a9940e417a09832f10253cd69ad82c01
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