Feature Extraction
sentence-transformers
PyTorch
English
bert
splade
sparse-encoder
sparse
text-embeddings-inference
Instructions to use naver/splade-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use naver/splade-v3 with sentence-transformers:
from sentence_transformers import SparseEncoder model = SparseEncoder("naver/splade-v3") queries = ["Which planet is known as the Red Planet?"] documents = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", ] query_embeddings = model.encode_query(queries) document_embeddings = model.encode_document(documents) similarities = model.similarity(query_embeddings, document_embeddings) print(similarities) - Inference
- Notebooks
- Google Colab
- Kaggle
Loading `naver/splade-v3` model from transformer python library results in `ModuleNotFoundError`
#7
by sirfumi - opened
Hello team,
I want to do some experiments with the the splade-v3 model but are unable to load it.
How to reproduce the error:
- In a
python==3.11.11environment install HFtransformerslibrarytransformers==4.52.4correctly installed
- Provide HF Access Token to
transformerslibrary - Run the following code (
tokenizeris loaded correctly):
from transformers import AutoModelForMaskedLM, AutoTokenizer
# Load a pretrained SPLADE model and tokenizer from Hugging Face
model_id = "naver/splade-v3"
tokenizer = AutoTokenizer.from_pretrained(model_id)
- Now run
model = AutoModelForMaskedLM.from_pretrained(model_id)which causes the following error
ModuleNotFoundError: Could not import module 'BertForMaskedLM'. Are this object's requirements defined correctly?
I have already tried re-installing the transformers library, does anybody have a solution
Thank you in advance
Are you able to load a basic Bert model?
Hello @Herve , thank you for getting back to me.
Not only am I able to load the basic BERT model, but loading it before the splade-v3 seems to fix the issue.
I deleted the cache and it seems that by adding from transformers import BertForMaskedLM makes the script work (even without creating any instance of it).
New code that works:
from transformers import (
AutoModelForMaskedLM,
AutoTokenizer,
BertForMaskedLM
)
# %% Load a pretrained SPLADE model and tokenizer from Hugging Face
model_id = "naver/splade-v3"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForMaskedLM.from_pretrained(model_id)
Do you have any explanation for this?