Instructions to use amberoad/bert-multilingual-passage-reranking-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amberoad/bert-multilingual-passage-reranking-msmarco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="amberoad/bert-multilingual-passage-reranking-msmarco")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("amberoad/bert-multilingual-passage-reranking-msmarco") model = AutoModelForSequenceClassification.from_pretrained("amberoad/bert-multilingual-passage-reranking-msmarco") - Inference
- Notebooks
- Google Colab
- Kaggle
ATTENTION to everyone
#4
by Xingxingxingxing - opened
this model is wrong. the output dimension is 2. Do not waste your time to use this model.
@Xingxingxingxing
As I haven't touched this model on my own in nearly 3 years, I honestly can't answer your question, but as the model was picked up and evaluated in multiple peer reviewed papers (e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9090691/) I guess that it is right and the output is as expected.
Philipp changed discussion status to closed