Sentence Similarity
sentence-transformers
Safetensors
French
xlm-roberta
passage-retrieval
pruned
text-embeddings-inference
Instructions to use antoinelouis/french-me5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use antoinelouis/french-me5-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("antoinelouis/french-me5-large") sentences = [ "C'est une personne heureuse", "C'est un chien heureux", "C'est une personne très heureuse", "Aujourd'hui est une journée ensoleillée" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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---
pipeline_tag: sentence-similarity
language: fr
license: mit
tags:
- passage-retrieval
- sentence-similarity
- pruned
library_name: sentence-transformers
base_model: intfloat/multilingual-e5-large
base_model_relation: quantized
---
# 🇫🇷 french-me5-large
This model is a 38.9% smaller version of [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large)
for the French language, created using the [mtem-pruner](https://huggingface.co/spaces/antoinelouis/mtem-pruner) space.
This pruned model should perform similarly to the original model for French language tasks with a much smaller
memory footprint. However, it may not perform well for other languages present in the original multilingual model as tokens not
commonly used in French were removed from the original multilingual model's vocabulary.
## Usage
You can use this model with the Transformers library:
```python
from transformers import AutoModel, AutoTokenizer
model_name = "antoinelouis/french-multilingual-e5-large"
model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True, use_fast=True)
```
Or with the sentence-transformers library:
```python
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("antoinelouis/french-multilingual-e5-large")
```
**Credits**: cc [@antoinelouis](https://huggingface.co/antoinelouis)
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