Instructions to use NLP-EXP/QST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-EXP/QST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-EXP/QST")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QST") model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NLP-EXP/QST: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/NLP-EXP/QST/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NLP-EXP/QST/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NLP-EXP/QST/resolve/main/pytorch_model.bin
541 MB
- Xet hash:
- a6076b2718873952f08f428821b7035ff5557a5bdbc8e5d8f24800c0c4ba4e69
- Size of remote file:
- 541 MB
- SHA256:
- 30d9518c826c7759f08b23fc6dd70cd39098f14c4e1f202e558c2e6faee241f0
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