Instructions to use djinnn/Bhasa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djinnn/Bhasa_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("djinnn/Bhasa_model") model = AutoModelForSeq2SeqLM.from_pretrained("djinnn/Bhasa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from djinnn/Bhasa_model: direct link, hf CLI and curl.
- Browser
- Download file 2.95 GB
-
https://huggingface.co/djinnn/Bhasa_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://djinnn/Bhasa_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/djinnn/Bhasa_model/resolve/main/pytorch_model.bin
2.95 GB
- Xet hash:
- d051937085b5ccd898da5ff1fa59185f5b5f3560fc4413b450d209f1c35a6f34
- Size of remote file:
- 2.95 GB
- SHA256:
- f57995ad781ab482844f8a340368a83010d743c5e045046fe97213b6aed40283
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