Instructions to use Swamitucats/M2M101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Swamitucats/M2M101 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Swamitucats/M2M101") model = AutoModelForSeq2SeqLM.from_pretrained("Swamitucats/M2M101", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Swamitucats/M2M101: direct link, hf CLI and curl.
- Browser
- Download file 4.15 kB
-
https://huggingface.co/Swamitucats/M2M101/resolve/main/training_args.bin
- Command line
-
hf download hf://Swamitucats/M2M101/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Swamitucats/M2M101/resolve/main/training_args.bin
4.15 kB
- Xet hash:
- d539c9da18030d4b2ecf671a73db1c1eccdd086c3103f74d42a68f5315ddc7cb
- Size of remote file:
- 4.15 kB
- SHA256:
- 97fd8c0a47c83c02d648f96668cca457515a647b10d9f88b5149e912991708fd
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