Instructions to use julianubc/lab1_random with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use julianubc/lab1_random with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("julianubc/lab1_random") model = AutoModelForSeq2SeqLM.from_pretrained("julianubc/lab1_random", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c158be7514d30833b897ffca9934dbb13a6dd7c223ebf9428f160bfa8c3ffe6
- Size of remote file:
- 5.43 kB
- SHA256:
- 7ec0f3e203d86ecc81c58b53445e9597e0b57e2bb63ad81e044fad999096ac80
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