Add new SentenceTransformer model
Browse filesHello!
*This pull request has been automatically generated from the [`push_to_hub`](https://sbert.net/docs/package_reference/sentence_transformer/SentenceTransformer.html#sentence_transformers.SentenceTransformer.push_to_hub) method from the Sentence Transformers library.*
## Full Model Architecture:
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 8192, 'do_lower_case': False}) with Transformer model: ModernBertModel
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
(2): Normalize()
)
```
## Tip:
Consider testing this pull request before merging by loading the model from this PR with the `revision` argument:
```python
from sentence_transformers import SentenceTransformer
# TODO: Fill in the PR number
pr_number = 2
model = SentenceTransformer(
"lightonai/modernbert-embed-large",
revision=f"refs/pr/{pr_number}",
backend="torch",
)
# Verify that everything works as expected
embeddings = model.encode(["The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium."])
print(embeddings.shape)
similarities = model.similarity(embeddings, embeddings)
print(similarities)
```
- 1_Pooling/config.json +10 -0
- README.md +0 -0
- config.json +1 -1
- config_sentence_transformers.json +10 -0
- modules.json +20 -0
- sentence_bert_config.json +4 -0
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{
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"word_embedding_dimension": 1024,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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{
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"_name_or_path": "lightonai/modernbert-embed-large
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"architectures": [
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"ModernBertModel"
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],
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"_name_or_path": "lightonai/modernbert-embed-large",
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"architectures": [
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"ModernBertModel"
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],
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{
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"__version__": {
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"sentence_transformers": "3.4.0.dev0",
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"transformers": "4.48.0.dev0",
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"pytorch": "2.6.0.dev20241112+cu121"
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},
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"prompts": {},
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"default_prompt_name": null,
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"similarity_fn_name": "cosine"
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}
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[
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{
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"idx": 0,
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"name": "0",
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"path": "",
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"type": "sentence_transformers.models.Transformer"
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},
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{
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"idx": 1,
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"name": "1",
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"path": "1_Pooling",
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"type": "sentence_transformers.models.Pooling"
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},
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{
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"idx": 2,
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"name": "2",
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"path": "2_Normalize",
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"type": "sentence_transformers.models.Normalize"
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}
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]
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{
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"max_seq_length": 8192,
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"do_lower_case": false
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}
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