Feature Extraction
Transformers
Safetensors
ModularStarEncoder
custom_code
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  <!-- Provide a quick summary of what the model is/does. -->
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  ModularStarEncoder-finetuned is an encoder built on top of [ModularStarEncoder-1B Pre-trained](https://huggingface.co/andreagurioli1995/ModularStarEncoder) on [SynthCode2Code2NL](https://huggingface.co/datasets/andreagurioli1995/SynthCode2Code2NL-neardedup).
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- ModularStarEncoder fine-tuned is an encoder for various retrieval tasks, enabling the end user to select the model size that meets their memory and computational constraints.
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  We built ModularStarEncoder on top of [StarCoder-2](https://huggingface.co/bigcode/starcoder2-15b), reducing its size from 15B to 1B parameters in bfloat16.
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  The model is finetuned with [CLIP objective](https://github.com/mlfoundations/open_clip/blob/main/src/open_clip/loss.py).
 
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  <!-- Provide a quick summary of what the model is/does. -->
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  ModularStarEncoder-finetuned is an encoder built on top of [ModularStarEncoder-1B Pre-trained](https://huggingface.co/andreagurioli1995/ModularStarEncoder) on [SynthCode2Code2NL](https://huggingface.co/datasets/andreagurioli1995/SynthCode2Code2NL-neardedup).
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+ ModularStarEncoder, fine-tuned, is an encoder for code-to-code and nl-to-code retrieval tasks, enabling the end user to select the model size that meets their memory and computational constraints.
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  We built ModularStarEncoder on top of [StarCoder-2](https://huggingface.co/bigcode/starcoder2-15b), reducing its size from 15B to 1B parameters in bfloat16.
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  The model is finetuned with [CLIP objective](https://github.com/mlfoundations/open_clip/blob/main/src/open_clip/loss.py).