Instructions to use haochenhe/lab1_random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haochenhe/lab1_random with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("haochenhe/lab1_random") model = AutoModelForSeq2SeqLM.from_pretrained("haochenhe/lab1_random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2581f904dd746ebf2d60b21ba048845cec082d15aea25bb767b34dc91ce1428b
- Size of remote file:
- 4.73 kB
- SHA256:
- a7ad2c84baabffcae529260f66b8a905417f22761e70183ae3500a1f36d8b240
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.