Instructions to use LazarusNLP/indo-t5-base-nusax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LazarusNLP/indo-t5-base-nusax with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LazarusNLP/indo-t5-base-nusax") model = AutoModelForSeq2SeqLM.from_pretrained("LazarusNLP/indo-t5-base-nusax", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_results.json from LazarusNLP/indo-t5-base-nusax: direct link, hf CLI and curl.
- Browser
- Download file 241 Bytes
-
https://huggingface.co/LazarusNLP/indo-t5-base-nusax/resolve/main/eval_results.json
- Command line
-
hf download hf://LazarusNLP/indo-t5-base-nusax/eval_results.json
-
curl -L -o eval_results.json https://huggingface.co/LazarusNLP/indo-t5-base-nusax/resolve/main/eval_results.json
241 Bytes
| { | |
| "epoch": 6.02, | |
| "eval_bleu": 19.701, | |
| "eval_gen_len": 48.7964, | |
| "eval_loss": 2.260429859161377, | |
| "eval_runtime": 93.8695, | |
| "eval_samples": 4200, | |
| "eval_samples_per_second": 44.743, | |
| "eval_steps_per_second": 0.352 | |
| } |