Instructions to use slone/nllb-200-600M-tum-eng-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use slone/nllb-200-600M-tum-eng-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("slone/nllb-200-600M-tum-eng-v1") model = AutoModelForSeq2SeqLM.from_pretrained("slone/nllb-200-600M-tum-eng-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04072d52f0bb0d5262d6dc46533bcb392e6199632a1c694ac0a2df2c5d3e70b1
- Size of remote file:
- 2.46 GB
- SHA256:
- 5569b326b7606504fcd909a1c6fa4ba920752f65bf1dd867b567c5f816d3a055
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