Instructions to use CLAck/indo-mixed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLAck/indo-mixed with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="CLAck/indo-mixed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CLAck/indo-mixed") model = AutoModelForSeq2SeqLM.from_pretrained("CLAck/indo-mixed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CLAck/indo-mixed: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/CLAck/indo-mixed/resolve/71d7128837b1e62559dfdb321e4d8a70bf517f72/training_args.bin
- Command line
-
hf download hf://CLAck/indo-mixed@71d7128837b1e62559dfdb321e4d8a70bf517f72/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CLAck/indo-mixed/resolve/71d7128837b1e62559dfdb321e4d8a70bf517f72/training_args.bin
3.18 kB
- Xet hash:
- 7340c6938eca441da7ef4c1ad0c765bf54d848dd716ebcd373bbec0355e6bb29
- Size of remote file:
- 3.18 kB
- SHA256:
- 192bd2bd61e28f1ff2ebd1fd02ec3f13ef6c0aaa45032465b241d7b43878514f
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