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 pytorch_model.bin from Swamitucats/M2M101: direct link, hf CLI and curl.
- Browser
- Download file 1.94 GB
-
https://huggingface.co/Swamitucats/M2M101/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Swamitucats/M2M101/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Swamitucats/M2M101/resolve/main/pytorch_model.bin
1.94 GB
- Xet hash:
- 24462ee01d0fc9e0a6c20efb5011af1532927866ba52b1c66f34ee1c1c6c34cd
- Size of remote file:
- 1.94 GB
- SHA256:
- fad91c6ec8d984c36ac020a351a96697c53907e0aff0503d18c6a9b99f93b496
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