Instructions to use shadowlilac/t5g-ak with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shadowlilac/t5g-ak with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("shadowlilac/t5g-ak") model = AutoModelForMultimodalLM.from_pretrained("shadowlilac/t5g-ak", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from shadowlilac/t5g-ak: direct link, hf CLI and curl.
- Browser
- Download file 33.4 MB
-
https://huggingface.co/shadowlilac/t5g-ak/resolve/main/tokenizer.json
- Command line
-
hf download hf://shadowlilac/t5g-ak/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/shadowlilac/t5g-ak/resolve/main/tokenizer.json
33.4 MB
- Xet hash:
- e17a59ec50087dabbbfe6615aaac72326f8bd585a0562950584d37b2d10d3fad
- Size of remote file:
- 33.4 MB
- SHA256:
- f5b325224482ec441ec5fbe2a5ac08c3758e0f9605f6e54368e31f736fcfb01d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.