Transformers
PyTorch
t5
text2text-generation
Text2Text Generation
Business names
Recommendation system
text-generation-inference
Instructions to use abdelhalim/Rec_Business_Names with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdelhalim/Rec_Business_Names with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("abdelhalim/Rec_Business_Names") model = AutoModelForSeq2SeqLM.from_pretrained("abdelhalim/Rec_Business_Names", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d8f6c26bc925854afa985322879f89c2d0cfe78655ab05a248d2754178d0884
- Size of remote file:
- 484 MB
- SHA256:
- 61ad415e8b539475b9b110af29c71845191f0580ed88e583184b3acce6d6451e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.