Instructions to use NLP-EXP/QSE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-EXP/QSE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-EXP/QSE")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QSE") model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QSE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NLP-EXP/QSE: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/NLP-EXP/QSE/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NLP-EXP/QSE/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NLP-EXP/QSE/resolve/main/pytorch_model.bin
541 MB
- Xet hash:
- b9b5e94cd86c83599d95e0e2d0b393adcb872e6dbd596593b113631b53b82221
- Size of remote file:
- 541 MB
- SHA256:
- d4e2246c3765e1e50e3fecf6e4c62311a11a40a27407cca87ff173841a7ca426
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