Translation
Transformers
Safetensors
Indonesian
Gorontalo
mbart
text2text-generation
gorontalo
indonesian
bahasa-daerah
low-resource
seq2seq
nmt
hulontalo
Eval Results (legacy)
Instructions to use datanikah9/tuwili with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datanikah9/tuwili 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="datanikah9/tuwili")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("datanikah9/tuwili") model = AutoModelForSeq2SeqLM.from_pretrained("datanikah9/tuwili", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a619d87b54e41134e96e4030a524192e91f4d0355ab73cb392c1b465ae496cb7
- Size of remote file:
- 5.43 kB
- SHA256:
- 1e7a3c736df11fbd70917e52e2b44fcc7dc143a98dcf08d214c10cfdee4620d7
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