Instructions to use Python/ACROSS-m2o-eng-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Python/ACROSS-m2o-eng-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Python/ACROSS-m2o-eng-base") model = AutoModelForSeq2SeqLM.from_pretrained("Python/ACROSS-m2o-eng-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Python/ACROSS-m2o-eng-base: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/Python/ACROSS-m2o-eng-base/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://Python/ACROSS-m2o-eng-base@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Python/ACROSS-m2o-eng-base/resolve/refs%2Fpr%2F1/model.safetensors
2.33 GB
- Xet hash:
- 845d2ec4783638f339da9b8b383621ce569a339507e5942289707206299c333a
- Size of remote file:
- 2.33 GB
- SHA256:
- 0a5fbfe843951e5b9fb06740d6b6a36dcfc11de228059165d9956e675c2be64f
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