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Instructions to use naver/efficient-splade-VI-BT-large-query with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
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How to use naver/efficient-splade-VI-BT-large-query with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="naver/efficient-splade-VI-BT-large-query")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("naver/efficient-splade-VI-BT-large-query") model = AutoModelForMaskedLM.from_pretrained("naver/efficient-splade-VI-BT-large-query") - Inference
- Notebooks
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Add sentence-transformers library_name and filtering tags
#3
by tomaarsen HF Staff - opened
Hello!
Pull Request Overview
- Add library_name, filtering tags, and pipeline_tag
Details
We forgot to include this in a prior PR, meaning that this model didn't yet show up when filtering for sparse Sentence Transformer models here: https://huggingface.co/models?library=sentence-transformers&other=sparse
cc @tformal
- Tom Aarsen