Sentence Similarity
sentence-transformers
Safetensors
French
xlm-roberta
passage-retrieval
pruned
text-embeddings-inference
Instructions to use Gameselo/french-multilingual-e5-large-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Gameselo/french-multilingual-e5-large-instruct with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Gameselo/french-multilingual-e5-large-instruct") 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
🇫🇷 french-multilingual-e5-large-instruct
This model is a 38.9% smaller version of intfloat/multilingual-e5-large-instruct for the French language, created using the 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:
from transformers import AutoModel, AutoTokenizer
model_name = "Gameselo/french-multilingual-e5-large-instruct"
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:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Gameselo/french-multilingual-e5-large-instruct")
Credits: cc @antoinelouis
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Model tree for Gameselo/french-multilingual-e5-large-instruct
Base model
intfloat/multilingual-e5-large-instruct