Instructions to use adiom/avrora-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adiom/avrora-1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("adiom/avrora-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from adiom/avrora-1: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/adiom/avrora-1/resolve/main/tokenizer.json
- Command line
-
hf download hf://adiom/avrora-1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/adiom/avrora-1/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 922b7ca7ba4d2f66d92f0b1191fe3a4010a67fe8265e9c69b1d65f60f9970339
- Size of remote file:
- 34.4 MB
- SHA256:
- f559f2189f392b4555613965f089e7c4d300b41fbe080bf79da0d676e33ee7f0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.