Instructions to use ielabgroup/BiTAG-t5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ielabgroup/BiTAG-t5-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ielabgroup/BiTAG-t5-large") model = AutoModelForSeq2SeqLM.from_pretrained("ielabgroup/BiTAG-t5-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a4b14f1d8cb46259b7cda66494705ff5d2a82064fb6d86f8cc631753b869516
- Size of remote file:
- 2.95 GB
- SHA256:
- 94b2fc7482cdb8fe75f6d48c0e88b49fa514eff727508683370731c66fdab55a
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