Instructions to use utahnlp/robertabase-structured-tuning-srl-conll2012 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use utahnlp/robertabase-structured-tuning-srl-conll2012 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RobertaForSRL tokenizer = AutoTokenizer.from_pretrained("utahnlp/robertabase-structured-tuning-srl-conll2012") model = RobertaForSRL.from_pretrained("utahnlp/robertabase-structured-tuning-srl-conll2012", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Create README.md (#2)
- Create README.md (dbb49fbe7a72fb19d9c5fb6113bc2c7a7785f0a4) Co-authored-by: Tao Li <t-li@users.noreply.huggingface.co>788c03d
-
allow flax
0045621
-
Update pytorch_model.bin
5dfc831 -
Update merges.txt
b12b65a -
Update special_tokens_map.json
169663f -
Update vocab.json
b1af972 -
Update tokenizer_config.json
bc6e120 -
Update config.json
75e50a1 -
initial commit
fc20a9e