Instructions to use ArjanvD95/animals_mdeberta_s42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArjanvD95/animals_mdeberta_s42 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ArjanvD95/animals_mdeberta_s42")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ArjanvD95/animals_mdeberta_s42") model = AutoModelForTokenClassification.from_pretrained("ArjanvD95/animals_mdeberta_s42") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c20427c4d79fcb7d6f1ab48c53e80993f7654bbaa3d52e23bcc6b1d10330c08
- Size of remote file:
- 5.24 kB
- SHA256:
- cbf322a8ce0506a66ef82cfcf3e9b6190aa9b03c95f1293cc6bc2302cde66eca
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.