Instructions to use Narsil/small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Narsil/small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Narsil/small") model = AutoModelForTokenClassification.from_pretrained("Narsil/small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from Narsil/small: direct link, hf CLI and curl.
- Browser
- Download file 297 kB
-
https://huggingface.co/Narsil/small/resolve/main/tf_model.h5
- Command line
-
hf download hf://Narsil/small/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/Narsil/small/resolve/main/tf_model.h5
297 kB
- Xet hash:
- bfaf073a559f629df98f2fa60b1c698c4c6a08d0ba3c0188ac43e54bc2ea22e7
- Size of remote file:
- 297 kB
- SHA256:
- eda32354aefc3b2aca8f0384aac512b9d0c3b05576c57ae7607035afdc083f24
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