Instructions to use joshanashakya/codebert_sourcecode_nmt_ja2pn_50E_2e-05LR_16B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joshanashakya/codebert_sourcecode_nmt_ja2pn_50E_2e-05LR_16B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("joshanashakya/codebert_sourcecode_nmt_ja2pn_50E_2e-05LR_16B") model = AutoModelForSeq2SeqLM.from_pretrained("joshanashakya/codebert_sourcecode_nmt_ja2pn_50E_2e-05LR_16B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from joshanashakya/codebert_sourcecode_nmt_ja2pn_50E_2e-05LR_16B: direct link, hf CLI and curl.
- Browser
- Download file 3.18 kB
-
https://huggingface.co/joshanashakya/codebert_sourcecode_nmt_ja2pn_50E_2e-05LR_16B/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://joshanashakya/codebert_sourcecode_nmt_ja2pn_50E_2e-05LR_16B@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/joshanashakya/codebert_sourcecode_nmt_ja2pn_50E_2e-05LR_16B/resolve/refs%2Fpr%2F1/training_args.bin
3.18 kB
- Xet hash:
- 3e9ec8de263063870a00c6de6d9939f0fcf080d48f781bb59624724797418177
- Size of remote file:
- 3.18 kB
- SHA256:
- 3f7dedc4ee408db437370904505347a54d06af41c23bc8784ea573f14453db31
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