Instructions to use Peramanathan/cv-qa-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Peramanathan/cv-qa-model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Peramanathan/cv-qa-model") model = AutoModelForSeq2SeqLM.from_pretrained("Peramanathan/cv-qa-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Peramanathan/cv-qa-model: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/Peramanathan/cv-qa-model/resolve/main/training_args.bin
- Command line
-
hf download hf://Peramanathan/cv-qa-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Peramanathan/cv-qa-model/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- f67c7d83086303c6613338566704f05cd9b4826314f23c63f0cbdb228b6c53ee
- Size of remote file:
- 5.91 kB
- SHA256:
- 600b8ae5c2df9a2cbb061b7bcad04e5ea3f7edfd6965442e2e30d0500813fa57
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