Instructions to use egoitz/roberta-timex-semeval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use egoitz/roberta-timex-semeval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="egoitz/roberta-timex-semeval")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("egoitz/roberta-timex-semeval") model = AutoModelForTokenClassification.from_pretrained("egoitz/roberta-timex-semeval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from egoitz/roberta-timex-semeval: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/egoitz/roberta-timex-semeval/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://egoitz/roberta-timex-semeval/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/egoitz/roberta-timex-semeval/resolve/main/flax_model.msgpack
496 MB
- Xet hash:
- 1e53207fecba7b554f36413aee91acf66ed982c380fc524f8a18837b269b3e5c
- Size of remote file:
- 496 MB
- SHA256:
- 8fae6c5ae2e5956b270eb407eebb8ff4aa513a714d7c0234473b900ab758840b
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