Text Retrieval
sentence-transformers
Safetensors
English
new
embeddings
agent
search
retriever
instruction-tuned retriever
agentic-search
custom_code
Instructions to use zarif98sjs/Critic-Embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zarif98sjs/Critic-Embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zarif98sjs/Critic-Embed", trust_remote_code=True) sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Update model card: add pipeline tag, library name, and code link
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by nielsr HF Staff - opened
README.md
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license: cc-by-nc-4.0
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language:
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- en
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base_model:
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tags:
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- embeddings
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- agent
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# Critic-Embed
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Critic-Embed is the trained
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# Usage
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---
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base_model:
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- NovaSearch/stella_en_400M_v5
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language:
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- en
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license: cc-by-nc-4.0
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pipeline_tag: text-retrieval
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library_name: sentence-transformers
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tags:
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- embeddings
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- agent
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# Critic-Embed
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Critic-Embed is the trained retriever from the paper [Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback](https://arxiv.org/abs/2606.00590).
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**Code**: [https://github.com/zarif98sjs/Critic-R](https://github.com/zarif98sjs/Critic-R)
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# Usage
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