Instructions to use formermagic/codet5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use formermagic/codet5-large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("formermagic/codet5-large") model = AutoModelForSeq2SeqLM.from_pretrained("formermagic/codet5-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from formermagic/codet5-large: direct link, hf CLI and curl.
- Browser
- Download file 3.13 GB
-
https://huggingface.co/formermagic/codet5-large/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://formermagic/codet5-large/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/formermagic/codet5-large/resolve/main/flax_model.msgpack
3.13 GB
- Xet hash:
- 7997c48a804db97f479fd554f93496bd259217a65469f187351e5629ab4ee52b
- Size of remote file:
- 3.13 GB
- SHA256:
- 61f2e83b30ccf7aed84fc6d274277cb076a9b8367ec21b315d846d1a13392aee
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