Instructions to use astroa7m/AOU_BOT_SILMA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use astroa7m/AOU_BOT_SILMA with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("astroa7m/AOU_BOT_SILMA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from astroa7m/AOU_BOT_SILMA: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/astroa7m/AOU_BOT_SILMA/resolve/main/tokenizer.json
- Command line
-
hf download hf://astroa7m/AOU_BOT_SILMA/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/astroa7m/AOU_BOT_SILMA/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- a1d3a8eb24fbafe7e9a580d393e7fee4b3d9a980168a420f4d4d39b0ddf0b6cd
- Size of remote file:
- 34.4 MB
- SHA256:
- 3302bd9d1a4d85a54b03bcf3e723c087847b18f28e4af6932112d287e17bcb5c
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