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")# 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
- Xet hash:
- 8b9cb7cd4a3a8e10f097a14474bf70a2197af91b6866b866775c2952e5b931b1
- Size of remote file:
- 337 MB
- SHA256:
- 30f95cfd91943d5c0d871cfbbf4e97cef5e1fb95cc2102eaff4f662b948edf4d
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