Instructions to use benjamin/compoundpiece with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjamin/compoundpiece with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("benjamin/compoundpiece") model = AutoModelForSeq2SeqLM.from_pretrained("benjamin/compoundpiece", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from benjamin/compoundpiece: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/benjamin/compoundpiece/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://benjamin/compoundpiece/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/benjamin/compoundpiece/resolve/main/flax_model.msgpack
2.33 GB
- Xet hash:
- e4263664d9e933fe95834a693c3b2e892002e0a27b7c3cf416613092c4ae9238
- Size of remote file:
- 2.33 GB
- SHA256:
- d6f759ab38ad651e4dba05f67a6319106314e3affb559953036de58685915744
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