Instructions to use ucabqfe/roberta_PER_bieo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ucabqfe/roberta_PER_bieo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ucabqfe/roberta_PER_bieo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ucabqfe/roberta_PER_bieo") model = AutoModelForTokenClassification.from_pretrained("ucabqfe/roberta_PER_bieo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ucabqfe/roberta_PER_bieo: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/ucabqfe/roberta_PER_bieo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ucabqfe/roberta_PER_bieo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ucabqfe/roberta_PER_bieo/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- be820b1c8e29f7df8378b775d39e513472dce2507a2c95ac08e67bb06494784c
- Size of remote file:
- 496 MB
- SHA256:
- 71576d07f44aadabca1dae767bf09b299b5dcf121f9d024c18948eebdac419bc
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