Instructions to use Mayfull/Llava_Next_VLTopKSAE_20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mayfull/Llava_Next_VLTopKSAE_20 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import VLTopKSAE model = VLTopKSAE.from_pretrained("Mayfull/Llava_Next_VLTopKSAE_20", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Mayfull/Llava_Next_VLTopKSAE_20: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/Mayfull/Llava_Next_VLTopKSAE_20/resolve/main/tokenizer.json
- Command line
-
hf download hf://Mayfull/Llava_Next_VLTopKSAE_20/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Mayfull/Llava_Next_VLTopKSAE_20/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 497f8640a99b6ef2d4447cabc17a51729ec7c873ba4dd6630b0a2494d1bd2a9f
- Size of remote file:
- 17.2 MB
- SHA256:
- 6041bee5196ef11a4e3ee293a9b7eef55e3f130f8bad33e51063cbf58454454d
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