Instructions to use ndilsou/mbay_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ndilsou/mbay_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ndilsou/mbay_model") model = AutoModelForSeq2SeqLM.from_pretrained("ndilsou/mbay_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ndilsou/mbay_model: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/ndilsou/mbay_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ndilsou/mbay_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ndilsou/mbay_model/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- b1fade2ad5b441ba9c876cdc3e20d3e961b7911ffd4606f624dd3d8b91032c6a
- Size of remote file:
- 242 MB
- SHA256:
- 95128b0cbaf0a1c4a74e25fcfc9f0b6c59a2bdafbc21228088d64590118775b1
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