build(deps): bump sentence-transformers from 3.0.1 to 3.3.1 in /application

[dependabot]

Bumps sentence-transformers from 3.0.1 to 3.3.1.

Release notes

Sourced from sentence-transformers's releases.

v3.3.1 - Patch private model loading without environment variable

This patch release fixes a small issue with loading private models from Hugging Face using the token argument.

Install this version with

# Training + Inference
pip install sentence-transformers[train]==3.3.1
Inference only, use one of:
pip install sentence-transformers==3.3.1
pip install sentence-transformers[onnx-gpu]==3.3.1
pip install sentence-transformers[onnx]==3.3.1
pip install sentence-transformers[openvino]==3.3.1

Details

If you're loading model under this scenario:

• Your model is hosted on Hugging Face.
• Your model is private.
• You haven't set the HF_TOKEN environment variable via huggingface-cli login or some other approach.
• You're passing the token argument to SentenceTransformer to load the model.

Then you may have encountered a crash in v3.3.0. This should be resolved now.

All Changes

• [docs] Fix the prompt link to the training script by @​tomaarsen in UKPLab/sentence-transformers#3060
• [Fix] Resolve loading private Transformer model in version 3.3.0 by @​pesuchin in UKPLab/sentence-transformers#3058

Full Changelog: UKPLab/sentence-transformers@v3.3.0...v3.3.1

v3.2.1 - Patch CLIP loading, small ONNX fix, compatibility with other libraries

This patch release fixes some small bugs, such as related to loading CLIP models, automatic model card generation issues, and ensuring compatibility with third party libraries.

Install this version with

# Training + Inference
pip install sentence-transformers[train]==3.2.1
Inference only, use one of:
pip install sentence-transformers==3.2.1
pip install sentence-transformers[onnx-gpu]==3.2.1
pip install sentence-transformers[onnx]==3.2.1
pip install sentence-transformers[openvino]==3.2.1

Fixing Loading non-Transformer models

In v3.2.0, a non-Transformer based model (e.g. CLIP) would not load correctly if the model was saved in the root of the model repository/directory. This has been resolved in #3007.

Throw error if StaticEmbedding-based model is finetuned with incompatible losses

The following losses are not compatible with StaticEmbedding-based models:

... (truncated)

Commits

• f6922f0 Merge branch 'master' into v3.3-release, increment to v3.3.1
• e156f38 [Fix] Resolve loading private Transformer model in version 3.3.0 (#3058)
• e28f97d [docs] Fix the prompt link to the training script (#3060)
• c1775a6 Increment the development version
• ea49e01 Release v3.3.0
• 6347b75 Moved Model Card Callback init in Trainer to a separate function (#3047)
• 7ede83b [enh] Add Support for multiple adapters on Transformers-based models (#3046)
• 6baee57 [fix] Fix model loading inconsistency after Peft training by using PeftModel ...
• 7be3eac [feat] Trainer with prompts and prompt masking (#2964)
• 15d3898 [docs] Add some missing docs for include_prompt in Pooling (#3042)
• Additional commits viewable in compare view

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