Bump sentence-transformers from 2.2.2 to 2.3.0

[dependabot]

Bumps sentence-transformers from 2.2.2 to 2.3.0.

Release notes

Sourced from sentence-transformers's releases.

v2.3.0 - Bug fixes, improved model loading & Cached MNRL

This release focuses on various bug fixes & improvements to keep up with adjacent works like transformers and huggingface_hub. These are the key changes in the release:

Pushing models to the Hugging Face Hub (#2376)

Prior to Sentence Transformers v2.3.0, saving models to the Hugging Face Hub may have resulted in various errors depending on the versions of the dependencies. Sentence Transformers v2.3.0 introduces a refactor to save_to_hub to resolve these issues.

from sentence_transformers import SentenceTransformer
model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
...
model.save_to_hub("tomaarsen/all-MiniLM-L6-v2-quora")

pytorch_model.bin: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████| 90.9M/90.9M [00:06<00:00, 13.7MB/s]
Upload 1 LFS files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:07<00:00,  7.11s/it]

Model Loading

Efficient model loading (#2345)

Recently, transformers has shifted towards using safetensors files as their primary model file formats. Additionally, various other file formats are commonly used, such as PyTorch (pytorch_model.bin), Rust (rust_model.ot), Tensorflow (tf_model.h5) and ONNX (model.onnx).

Prior to Sentence Transformers v2.3.0, almost all files of a repository would be downloaded, even if theye are not strictly required. Since v2.3.0, only the strictly required files will be downloaded. For example, when loading sentence-transformers/all-MiniLM-L6-v2 which has its model weights in three formats (pytorch_model.bin, rust_model.ot, tf_model.h5), only pytorch_model.bin will be downloaded. Additionally, when downloading intfloat/multilingual-e5-small with two formats (model.safetensors, pytorch_model.bin), only model.safetensors will be downloaded.

from sentence_transformers import SentenceTransformer
model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")

Downloading modules.json: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████| 349/349 [00:00<?, ?B/s]
Downloading (…)ce_transformers.json: 100%|███████████████████████████████████████████████████████████████████████████████████████████| 116/116 [00:00<?, ?B/s]
Downloading README.md: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████| 10.6k/10.6k [00:00<?, ?B/s]
Downloading (…)nce_bert_config.json: 100%|█████████████████████████████████████████████████████████████████████████████████████████| 53.0/53.0 [00:00<?, ?B/s]
Downloading config.json: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████| 612/612 [00:00<?, ?B/s]
Downloading pytorch_model.bin: 100%|█████████████████████████████████████████████████████████████████████████████████████| 90.9M/90.9M [00:06<00:00, 15.0MB/s]
Downloading tokenizer_config.json: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 350/350 [00:00<?, ?B/s]
Downloading vocab.txt: 100%|███████████████████████████████████████████████████████████████████████████████████████████████| 232k/232k [00:00<00:00, 1.37MB/s]
Downloading tokenizer.json: 100%|██████████████████████████████████████████████████████████████████████████████████████████| 466k/466k [00:00<00:00, 4.61MB/s]
Downloading (…)cial_tokens_map.json: 100%|███████████████████████████████████████████████████████████████████████████████████████████| 112/112 [00:00<?, ?B/s]
Downloading 1_Pooling/config.json: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 190/190 [00:00<?, ?B/s]

[!NOTE]
This release updates the default cache location from ~/.cache/torch/sentence_transformers to the default cache location of transformers, i.e. ~/.cache/huggingface. You can still specify custom cache locations via the SENTENCE_TRANSFORMERS_HOME environment variable or the cache_folder argument. Additionally, by supporting newer versions of various dependencies (e.g. huggingface_hub), the cache format changed. A consequence is that the old cached models cannot be used in v2.3.0 onwards, and those models need to be redownloaded. Once redownloaded, an airgapped machine can load the model like normal despite having no internet access.

Loading custom models (#2398)

This release brings models with custom code to Sentence Transformers through trust_remote_code, such as jinaai/jina-embeddings-v2-base-en.

... (truncated)

Commits

• 1ec4902 Release v2.3.0
• a1ed49c Fix typo: decection -> detection (#2445)
• 9fdaa5a [docs] Add CachedMultipleNegativesRankingLoss to docs (#2442)
• 0116721 Resolve 2 typos in example (#2433)
• 93d6335 bump the minimum supported torch version to 1.11 (#2432)
• 2caa636 Add '@​k' at the end of csv file name (#2427)
• e757296 Replace _target_device with device in semantic search example (#2424)
• ed916fb Add revision to load a specific model version (#2419)
• 4b00a34 fixed type in msmarco-v3.md (#2417)
• 009869d Add GradCache + MNRL: Go beyond GPU-memory limit for MNRL (#1759)
• Additional commits viewable in compare view

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[dependabot]

Superseded by #12.