Instructions to use intm/codet5-small-go_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use intm/codet5-small-go_generation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("intm/codet5-small-go_generation") model = AutoModelForSeq2SeqLM.from_pretrained("intm/codet5-small-go_generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from intm/codet5-small-go_generation: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/intm/codet5-small-go_generation/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://intm/codet5-small-go_generation/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/intm/codet5-small-go_generation/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- 9962f05fe1509e84bfdb50ee34cce2a64de0be98a42f75eb7cc55530247ef919
- Size of remote file:
- 242 MB
- SHA256:
- 590a79c3aa75a5ec5b12a3fe8207a9cf8fd4320cbfd41cf8e2fd0ee8fa4130a1
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