Instructions to use ArjanvD95/animals_pfr_mdeberta_512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArjanvD95/animals_pfr_mdeberta_512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ArjanvD95/animals_pfr_mdeberta_512")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ArjanvD95/animals_pfr_mdeberta_512") model = AutoModelForTokenClassification.from_pretrained("ArjanvD95/animals_pfr_mdeberta_512") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec173449f6efc0a110d29ddab7f80373e8a08412da5c7a209f4167f59ae9b50a
- Size of remote file:
- 16.4 MB
- SHA256:
- 2e12ea7ef3c1bfd4b1fb977636226680b9fcf10ede02f869dec0a324a5b86dfb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.