chore(deps): Bump sentence-transformers from 3.3.1 to 3.4.0 in /backend/python/transformers

[dependabot]

Bumps sentence-transformers from 3.3.1 to 3.4.0.

Release notes

Sourced from sentence-transformers's releases.

v3.4.0 - Resolved memory leak when deleting a model & trainer; add Matryoshka & Cached loss compatibility; small features & bug fixes

This release resolves a memory leak when deleting a model & trainer, adds compatibility between the Cached... losses and the Matryoshka loss modifier, resolves numerous bugs, and adds several small features.

Install this version with

# Training + Inference
pip install sentence-transformers[train]==3.4.0
Inference only, use one of:
pip install sentence-transformers==3.4.0
pip install sentence-transformers[onnx-gpu]==3.4.0
pip install sentence-transformers[onnx]==3.4.0
pip install sentence-transformers[openvino]==3.4.0

Matryoshka & Cached loss compatibility (#3068, #3107)

It is now possible to combine the strong Cached losses (CachedMultipleNegativesRankingLoss, CachedGISTEmbedLoss, CachedMultipleNegativesSymmetricRankingLoss) with the Matryoshka loss modifier:

from sentence_transformers import SentenceTransformer, SentenceTransformerTrainer, losses
from datasets import Dataset
model = SentenceTransformer("microsoft/mpnet-base")
train_dataset = Dataset.from_dict({
"anchor": ["It's nice weather outside today.", "He drove to work."],
"positive": ["It's so sunny.", "He took the car to the office."],
})
loss = losses.CachedMultipleNegativesRankingLoss(model, mini_batch_size=16)
loss = losses.MatryoshkaLoss(model, loss, [768, 512, 256, 128, 64])
trainer = SentenceTransformerTrainer(
model=model,
train_dataset=train_dataset,
loss=loss,
)
trainer.train()

See for example tomaarsen/mpnet-base-gooaq-cmnrl-mrl which was trained with CachedMultipleNegativesRankingLoss (CMNRL) with the Matryoshka loss modifier (MRL).

Resolve memory leak when Model and Trainer are reinitialized (#3144)

Due to a circular dependency in the SentenceTransformerTrainer -> SentenceTransformer -> SentenceTransformerModelCardData -> SentenceTransformerTrainer, deleting the trainer and model still doesn't clear them up via garbage disposal. I've moved a lot of components around, and now SentenceTransformerModelCardData does not need to store the SentenceTransformerTrainer, breaking the cycle.

We ran the seed optimization script (which frequently creates and deletes models and trainers):

• Before: Approximate highest recorded VRAM:

  16332MiB /  24576MiB
  

• After: Approximate highest recorded VRAM:

... (truncated)

Commits

• 90be5b7 Merge branch 'master' of https://github.com/UKPLab/sentence-transformers into...
• f4dc7b5 [docs] Update the documentation surrounding Matryoshka + Cached losses (#3190)
• d13c31e Add notes into tips at the top of sbert.net
• f443625 Add notes into tips at the top of sbert.net
• 6d9abff Release v3.4.0
• b1f1d03 [deprecation] Clarify that datasets and readers are deprecated since v3 (#3...
• 7056137 [tests] Make TripletEvaluator test more consistent (#3183)
• 57395b4 [docs] Add PEFT documentation + training example (#3180)
• 8073374 testcases for community detection (#3163)
• c68bf68 [fix] Use HfArgumentParser-compatible typing for prompts (#3178)
• Additional commits viewable in compare view

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