Instructions to use josh-oo/custom-decoder-ats with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use josh-oo/custom-decoder-ats with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("josh-oo/custom-decoder-ats", trust_remote_code=True) model = AutoModelForSeq2SeqLM.from_pretrained("josh-oo/custom-decoder-ats", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.e6cf81f
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Update README.md (#1)
- Update README.md (099acecc9c01b7345a43e4316ff30aa25502b5e7) Co-authored-by: Miriam Anschütz <MiriUll@users.noreply.huggingface.co>cd3f9d0
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Create README.md
96fb662 -
Added modified mBART tokenizer
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mBART + fine-tuned dbmdz/german-gpt2
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mBART + fine-tuned benjamin/gerpt2
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initial commit
Joshua Oehms73c2f58