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:
- 6165ca4720fcd5ab9ae48b46ba14aa0eac06af13d193cf1e1aa3cadcf616c9e6
- Size of remote file:
- 5.43 kB
- SHA256:
- 0c2165345bd3ad66bc55e439667f4213439d3fde971c615124fdb75a699b93b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.