Instructions to use HARISH20205/ResumeATS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HARISH20205/ResumeATS with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HARISH20205/ResumeATS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from HARISH20205/ResumeATS: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/HARISH20205/ResumeATS/resolve/main/tokenizer.json
- Command line
-
hf download hf://HARISH20205/ResumeATS/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/HARISH20205/ResumeATS/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 939f65686e00944e23120500331047b538b4fe4ab7b8c47d6bcc6d3b8cfe75c9
- Size of remote file:
- 17.2 MB
- SHA256:
- e9d7cacaa40afe2956f08737f84e63925c473cf6675d90dfc8caeae75768f9b7
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