Instructions to use Roasters/Answer-Predictor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Roasters/Answer-Predictor with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Roasters/Answer-Predictor") model = AutoModelForSeq2SeqLM.from_pretrained("Roasters/Answer-Predictor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Roasters/Answer-Predictor: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/Roasters/Answer-Predictor/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Roasters/Answer-Predictor@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Roasters/Answer-Predictor/resolve/refs%2Fpr%2F1/pytorch_model.bin
242 MB
- Xet hash:
- 0ec8c30bdfd940622f49e8ffb50bfeba23b95c9f40f561245ec22eff79e520b7
- Size of remote file:
- 242 MB
- SHA256:
- b8ff707312b9952c9872bbad8ccbd93fea10e0c19df835087fc931481047916a
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