Instructions to use kbnlresearch/indo2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kbnlresearch/indo2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kbnlresearch/indo2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kbnlresearch/indo2") model = AutoModelForMaskedLM.from_pretrained("kbnlresearch/indo2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kbnlresearch/indo2: direct link, hf CLI and curl.
- Browser
- Download file 712 MB
-
https://huggingface.co/kbnlresearch/indo2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kbnlresearch/indo2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kbnlresearch/indo2/resolve/main/pytorch_model.bin
712 MB
- Xet hash:
- ea587ab3d75dee4d7f74a3c3a5278b5f3eb5edbd3f1ca067262dc19b4d37926e
- Size of remote file:
- 712 MB
- SHA256:
- 068405383bef65839e0671a8ac461f116a74e184a2a60a588a32a800845ac081
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