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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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- **Paper:** [Link](arxiv.paper)
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- **Languages:** English, Go, Ruby, Python, Java, C++, PHP, C, JavaScript
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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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ModularStarEncoder fine-tuned works with instruction prompts; to get the most out of the model, embed the task in the input. The How to Use section below provides more details.
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- **Paper:** [Link](arxiv.paper)
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- **Languages:** English, Go, Ruby, Python, Java, C++, PHP, C, JavaScript
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