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
Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers`
#6 opened about 1 year ago
by
tomaarsen
Can this model be fine-tuned? Is there any sample code for fine-tuning?
#5 opened about 2 years ago
by
biaodiluer
Why is there 2 out_features in the classifier ?
➕ 1
4
#3 opened over 2 years ago
by
Adovilla
Adding `safetensors` variant of this model
#2 opened about 3 years ago
by
SFconvertbot