Instructions to use NLP-EXP/QE3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-EXP/QE3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-EXP/QE3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP-EXP/QE3") model = AutoModelForMaskedLM.from_pretrained("NLP-EXP/QE3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NLP-EXP/QE3: direct link, hf CLI and curl.
- Browser
- Download file 541 MB
-
https://huggingface.co/NLP-EXP/QE3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NLP-EXP/QE3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NLP-EXP/QE3/resolve/main/pytorch_model.bin
541 MB
- Xet hash:
- 79752abd2670e2718730e6514500f228bf62033d474cf971813923512cb1f7db
- Size of remote file:
- 541 MB
- SHA256:
- 6d560c8daf4b2892d1c8df6f2f246d5f58a8131bb177fcce2ad3c5556e35bbe1
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