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 tokenizer_config.json from Narsil/small: direct link, hf CLI and curl.
- Browser
- Download file 352 Bytes
-
https://huggingface.co/Narsil/small/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Narsil/small/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Narsil/small/resolve/main/tokenizer_config.json
352 Bytes
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "max_len": 512, "special_tokens_map_file": "/home/nicolas/.cache/torch/transformers/7ed0658a09e4f9689057c83f8b734d0e8d739f73461c7b7d1bc403aa451e304b.275045728fbf41c11d3dae08b8742c054377e18d92cc7b72b6351152a99b64e4", "tokenizer_file": null} |