Instructions to use dzinampini/code-to-json-documentor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzinampini/code-to-json-documentor with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dzinampini/code-to-json-documentor") model = AutoModelForSeq2SeqLM.from_pretrained("dzinampini/code-to-json-documentor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dzinampini/code-to-json-documentor: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/dzinampini/code-to-json-documentor/resolve/main/training_args.bin
- Command line
-
hf download hf://dzinampini/code-to-json-documentor/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dzinampini/code-to-json-documentor/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- c9b4bc5f7be010b9c34fed328cab951d5d17138069699b22f738cd1252b4831f
- Size of remote file:
- 5.43 kB
- SHA256:
- e33ea01a1ee9f6202219c8f2a231a002b482a00bb2de7ab45d68c8b80a97d301
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