Instructions to use NaoS2/multi-kogi2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NaoS2/multi-kogi2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NaoS2/multi-kogi2") model = AutoModelForSeq2SeqLM.from_pretrained("NaoS2/multi-kogi2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from NaoS2/multi-kogi2: direct link, hf CLI and curl.
- Browser
- Download file 4.46 MB
-
https://huggingface.co/NaoS2/multi-kogi2/resolve/main/spiece.model
- Command line
-
hf download hf://NaoS2/multi-kogi2/spiece.model
-
curl -L -o spiece.model https://huggingface.co/NaoS2/multi-kogi2/resolve/main/spiece.model
4.46 MB
- Xet hash:
- 257f9428970291f460b4256d8b651894a510d02d37d8999a131459792e82c513
- Size of remote file:
- 4.46 MB
- SHA256:
- f1763d314cf51284a7f50a71231d8d364145dbd0bfb2c3f74b95f33c218a656e
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