Instructions to use jpohhhh/embeddings_from_msmarco-MiniLM-L-6-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jpohhhh/embeddings_from_msmarco-MiniLM-L-6-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="jpohhhh/embeddings_from_msmarco-MiniLM-L-6-v3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jpohhhh/embeddings_from_msmarco-MiniLM-L-6-v3") model = AutoModel.from_pretrained("jpohhhh/embeddings_from_msmarco-MiniLM-L-6-v3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +2 -2
config.json
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{
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"_name_or_path": "sentence-transformers/
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"architectures": [
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"BertModel"
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],
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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{
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"_name_or_path": "sentence-transformers/all-MiniLM-L6-v2",
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"architectures": [
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"BertModel"
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],
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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