Instructions to use Narsil/small3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/small3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Narsil/small3")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Narsil/small3") model = AutoModelForTokenClassification.from_pretrained("Narsil/small3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3aaab2fff65c4fb8c61b2389b44f85ad2701dc555215d1212c8631bc961776f4
- Size of remote file:
- 146 kB
- SHA256:
- 4e6c5a850287ee371b9c2c74ba1c9b10a85ce0436c0e53685903caa635dd2aa3
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