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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("thatdramebaazguy/roberta-base-MITmovie") model = AutoModelForTokenClassification.from_pretrained("thatdramebaazguy/roberta-base-MITmovie", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from thatdramebaazguy/roberta-base-MITmovie: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/thatdramebaazguy/roberta-base-MITmovie/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://thatdramebaazguy/roberta-base-MITmovie/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/thatdramebaazguy/roberta-base-MITmovie/resolve/main/flax_model.msgpack
496 MB
- Xet hash:
- c47922e6294ef55812fdb2a9a57325a5bd70c12d06359edbe912ca3aee8d931d
- Size of remote file:
- 496 MB
- SHA256:
- 2510cb127093b5ca520fcd1ec41b5d2da1033a426012ca7f553d1c401d207a0e
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