florian-hoenicke commited on
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babb34b
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feat: push custom model

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1_Pooling/config.json ADDED
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+ {
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+ "word_embedding_dimension": 384,
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+ "pooling_mode_cls_token": true,
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - fine-tuned/BAAI_bge-small-en-v1_5-5252024-jzfp-webapp
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+ - allenai/c4
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+ language:
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+ - en
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+ pipeline_tag: feature-extraction
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+ tags:
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+ - sentence-transformers
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+ - feature-extraction
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+ - sentence-similarity
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+ - mteb
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+ - Cloud
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+ - Performance
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+ - Cost
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+ - Benchmark
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+ - Analysis
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+ ---
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+ This model is a fine-tuned version of [**BAAI/bge-small-en-v1.5**](https://huggingface.co/BAAI/bge-small-en-v1.5) designed for the following use case:
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+
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+ cloud provider product performance and cost analysis
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+
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+ ## How to Use
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+ This model can be easily integrated into your NLP pipeline for tasks such as text classification, sentiment analysis, entity recognition, and more. Here's a simple example to get you started:
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+
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+ ```python
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+ from sentence_transformers import SentenceTransformer
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+ from sentence_transformers.util import cos_sim
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+
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+ model = SentenceTransformer(
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+ 'fine-tuned/BAAI_bge-small-en-v1_5-5252024-jzfp-webapp',
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+ trust_remote_code=True
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+ )
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+
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+ embeddings = model.encode([
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+ 'first text to embed',
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+ 'second text to embed'
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+ ])
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+ print(cos_sim(embeddings[0], embeddings[1]))
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+ ```
config.json ADDED
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+ {
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+ }
config_sentence_transformers.json ADDED
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+ {
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+ "__version__": {
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tokenizer.json ADDED
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vocab.txt ADDED
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