Instructions to use WaiLwin/senior_mininet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WaiLwin/senior_mininet with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WaiLwin/senior_mininet", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.model from WaiLwin/senior_mininet: direct link, hf CLI and curl.
- Browser
- Download file 500 kB
-
https://huggingface.co/WaiLwin/senior_mininet/resolve/c052d9f7cdc7fb87e87f1f3643792bee798ade9c/tokenizer.model
- Command line
-
hf download hf://WaiLwin/senior_mininet@c052d9f7cdc7fb87e87f1f3643792bee798ade9c/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/WaiLwin/senior_mininet/resolve/c052d9f7cdc7fb87e87f1f3643792bee798ade9c/tokenizer.model
500 kB
- Xet hash:
- 91bf184ab12793d0754344f9095332759432e666320cc6c07f637af50e36db6f
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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