Instructions to use luohy/rgx-qg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luohy/rgx-qg with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("luohy/rgx-qg") model = AutoModelForSeq2SeqLM.from_pretrained("luohy/rgx-qg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from luohy/rgx-qg: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/luohy/rgx-qg/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://luohy/rgx-qg@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/luohy/rgx-qg/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.63 GB
- Xet hash:
- 2df364f1162ca38bdd082f4e763a27d5ccbcb07c42a5c35e0ce55410f657769c
- Size of remote file:
- 1.63 GB
- SHA256:
- e5f6c65223f53d6c9d47473751dd64a66781d572cc6d51ad8d63a2c5572c39f5
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