Instructions to use szymonpindur/herbert-onom-interjection-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use szymonpindur/herbert-onom-interjection-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="szymonpindur/herbert-onom-interjection-recognition")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("szymonpindur/herbert-onom-interjection-recognition") model = AutoModelForTokenClassification.from_pretrained("szymonpindur/herbert-onom-interjection-recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from szymonpindur/herbert-onom-interjection-recognition: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/szymonpindur/herbert-onom-interjection-recognition/resolve/main/training_args.bin
- Command line
-
hf download hf://szymonpindur/herbert-onom-interjection-recognition/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/szymonpindur/herbert-onom-interjection-recognition/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 53d756ef9e517c8bee538c9af9ad8be28b956ecd3d1a77236d3964d35b395c50
- Size of remote file:
- 3.52 kB
- SHA256:
- 3d2f97ba961bd0434f8d95773e2944be03aa0857bf04ffd906dd00c6f58e9767
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