| |
|
| | --- |
| | 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-multilingual-e5-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 = "aureliend/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("aureliend/french-multilingual-e5-large") |
| | ``` |
| |
|
| | **Credits**: cc [@antoinelouis](https://huggingface.co/antoinelouis) |
| |
|