crossencoder-camembert-large-mmarcoFR

110.8K

1

514

Small context

335M

1 language

license:mit

by

antoinelouis

Embedding Model

OTHER

Good

111K downloads

Production-ready

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

1GB+ RAM

Mobile

Laptop

Server

Quick Summary

This is a cross-encoder model for French.

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

1GB+ RAM

Code Examples

Using Sentence-Transformerspython

from sentence_transformers import CrossEncoder

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

model = CrossEncoder('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = model.predict(pairs)
print(scores)

Using Sentence-Transformerspython

from sentence_transformers import CrossEncoder

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

model = CrossEncoder('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = model.predict(pairs)
print(scores)

Using Sentence-Transformerspython

from sentence_transformers import CrossEncoder

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

model = CrossEncoder('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = model.predict(pairs)
print(scores)

Using Sentence-Transformerspython

from sentence_transformers import CrossEncoder

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

model = CrossEncoder('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = model.predict(pairs)
print(scores)

Using Sentence-Transformerspython

from sentence_transformers import CrossEncoder

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

model = CrossEncoder('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = model.predict(pairs)
print(scores)

Using Sentence-Transformerspython

from sentence_transformers import CrossEncoder

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

model = CrossEncoder('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = model.predict(pairs)
print(scores)

Using Sentence-Transformerspython

from sentence_transformers import CrossEncoder

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

model = CrossEncoder('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = model.predict(pairs)
print(scores)

Using Sentence-Transformerspython

from sentence_transformers import CrossEncoder

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

model = CrossEncoder('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = model.predict(pairs)
print(scores)

Using FlagEmbeddingpython

from FlagEmbedding import FlagReranker

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

reranker = FlagReranker('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = reranker.compute_score(pairs)
print(scores)

Using FlagEmbeddingpython

from FlagEmbedding import FlagReranker

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

reranker = FlagReranker('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = reranker.compute_score(pairs)
print(scores)

Using FlagEmbeddingpython

from FlagEmbedding import FlagReranker

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

reranker = FlagReranker('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = reranker.compute_score(pairs)
print(scores)

Using FlagEmbeddingpython

from FlagEmbedding import FlagReranker

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

reranker = FlagReranker('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = reranker.compute_score(pairs)
print(scores)

Using FlagEmbeddingpython

from FlagEmbedding import FlagReranker

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

reranker = FlagReranker('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = reranker.compute_score(pairs)
print(scores)

Using FlagEmbeddingpython

from FlagEmbedding import FlagReranker

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

reranker = FlagReranker('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = reranker.compute_score(pairs)
print(scores)

Using FlagEmbeddingpython

from FlagEmbedding import FlagReranker

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

reranker = FlagReranker('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = reranker.compute_score(pairs)
print(scores)

Using FlagEmbeddingpython

from FlagEmbedding import FlagReranker

pairs = [('Question', 'Paragraphe 1'), ('Question', 'Paragraphe 2') , ('Question', 'Paragraphe 3')]

reranker = FlagReranker('antoinelouis/crossencoder-camembert-large-mmarcoFR')
scores = reranker.compute_score(pairs)
print(scores)

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