Instructions to use adasgaleus/insertbert05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adasgaleus/insertbert05 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="adasgaleus/insertbert05")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("adasgaleus/insertbert05") model = AutoModelForTokenClassification.from_pretrained("adasgaleus/insertbert05", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from adasgaleus/insertbert05: direct link, hf CLI and curl.
- Browser
- Download file 3.45 kB
-
https://huggingface.co/adasgaleus/insertbert05/resolve/main/training_args.bin
- Command line
-
hf download hf://adasgaleus/insertbert05/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/adasgaleus/insertbert05/resolve/main/training_args.bin
3.45 kB
- Xet hash:
- 44e92508370a244a7b8dc7144546da9f6d76769d7ccce9a89055ece0d91cebfa
- Size of remote file:
- 3.45 kB
- SHA256:
- bdbb811c79416bdba3a193df5679d0097c9a29a3e2d2c93982a82a661c1fc6af
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