Instructions to use Narsil/small2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/small2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Narsil/small2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Narsil/small2") model = AutoModelForTokenClassification.from_pretrained("Narsil/small2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15ff878dec563960138b7fb9bf40b051f88acf66ef69aa35a45d2b00884c5268
- Size of remote file:
- 255 kB
- SHA256:
- c0d5e0aab7ed7c673eb12c7c0d41dbf3298dc1a5fcd5d7e07dfdd76e6a5e16b0
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