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 flax_model.msgpack from benjamin/compoundpiece-stage1: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/benjamin/compoundpiece-stage1/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://benjamin/compoundpiece-stage1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/benjamin/compoundpiece-stage1/resolve/main/flax_model.msgpack
2.33 GB
- Xet hash:
- aefc181ad2d0d30f27fd11a8e99b96cce63f6b65e743883c107c1819d35bb23f
- Size of remote file:
- 2.33 GB
- SHA256:
- 05ae4277899b6d54463c1a4f692ebf4be1cbd7984d1de9b5f84a14161a800921
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