Instructions to use Jiexing/spider_relation_t5_3b-4160 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jiexing/spider_relation_t5_3b-4160 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Jiexing/spider_relation_t5_3b-4160") model = AutoModelForSeq2SeqLM.from_pretrained("Jiexing/spider_relation_t5_3b-4160", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 705593ca7d9894329d955785a2cc5d88ce40442e4764ddad72c23be1189106b7
- Size of remote file:
- 13.6 MB
- SHA256:
- f83fa4073b763180d14a8cbbc873eeffb230d06a17ceda6c58f6d4551e8113e0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.