Token Classification
Transformers
PyTorch
TensorFlow
JAX
roberta
roberta-base
NER
named-entities
BIO
movies
Instructions to use thatdramebaazguy/roberta-base-MITmovie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thatdramebaazguy/roberta-base-MITmovie with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="thatdramebaazguy/roberta-base-MITmovie")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("thatdramebaazguy/roberta-base-MITmovie") model = AutoModelForTokenClassification.from_pretrained("thatdramebaazguy/roberta-base-MITmovie") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c47922e6294ef55812fdb2a9a57325a5bd70c12d06359edbe912ca3aee8d931d
- Size of remote file:
- 496 MB
- SHA256:
- 2510cb127093b5ca520fcd1ec41b5d2da1033a426012ca7f553d1c401d207a0e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.