Instructions to use alinankali/test_deploy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alinankali/test_deploy with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("alinankali/test_deploy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from alinankali/test_deploy: direct link, hf CLI and curl.
- Browser
- Download file 40 kB
-
https://huggingface.co/alinankali/test_deploy/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://alinankali/test_deploy/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/alinankali/test_deploy/resolve/main/tokenizer_config.json
40 kB
- Xet hash:
- e28b2ee11451a3da65030cecacd766222f84cdabe43bae6a019bbeb33c36c750
- Size of remote file:
- 40 kB
- SHA256:
- 4a0142fed3bd4dc1091236787a5e0a1825ac06b02b232365b14b45d0c1b96f98
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.