Instructions to use benjamin/compoundpiece-stage1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjamin/compoundpiece-stage1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("benjamin/compoundpiece-stage1") model = AutoModelForSeq2SeqLM.from_pretrained("benjamin/compoundpiece-stage1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from benjamin/compoundpiece-stage1: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/benjamin/compoundpiece-stage1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://benjamin/compoundpiece-stage1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/benjamin/compoundpiece-stage1/resolve/main/pytorch_model.bin
2.33 GB
- Xet hash:
- 1b262162de3331ba6aaeff9af22dcd85a12ebdfa9c7f0326a1ed2d145dbf1ebe
- Size of remote file:
- 2.33 GB
- SHA256:
- 9f52371ba6fe38aaaae24eb8321f23d805848674cf4e8f6daaad632af2bb2319
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