71 lines
2.5 KiB
Markdown
71 lines
2.5 KiB
Markdown
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---
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license: apache-2.0
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---
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<p style="font-size:20px;" align="center">
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<div style="width: 100%; height: 300px; overflow: hidden; border-radius: 15px; margin: auto; position: relative;">
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<img
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src="https://cdn.shuttleai.app/thumbnail.png"
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alt="ShuttleAI Thumbnail"
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style="width: 100%; height: auto; display: block; margin: auto; position: absolute; top: 50%; left: 50%; transform: translate(-50%, -50%); object-fit: cover;">
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</div>
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<p align="center">
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💻 <a href="https://shuttleai.app/" target="_blank">Use via API</a>
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</p>
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## Shuttle-2.5-mini (beta) [2024/07/27]
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We are excited to introduce Shuttle-2.5-mini, our next-generation state-of-the-art language model designed to excel in complex chat, multilingual communication, reasoning, and agent tasks.
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- **Shuttle-2.5-mini** is a fine-tuned version of [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407), emulating the writing style of Claude 3 models and thoroughly trained on role-playing data.
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## Model Details
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* **Model Name**: Shuttle-2.5-mini
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* **Developed by**: ShuttleAI Inc.
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* **Base Model**: [Mistral-Nemo-Base-2407](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407)
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* **Parameters**: 13B
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* **Language(s)**: Multilingual
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* **Repository**: [https://huggingface.co/shuttleai](https://huggingface.co/shuttleai)
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* **Fine-Tuned Model**: [https://huggingface.co/shuttleai/shuttle-2.5-mini](https://huggingface.co/shuttleai/shuttle-2.5-mini)
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* **Paper**: Shuttle-2.5-mini (Upcoming)
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* **License**: Apache 2.0
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## Base Model Architecture
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**Mistral Nemo** is a transformer model with the following architecture choices:
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- **Layers**: 40
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- **Dimension**: 5,120
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- **Head Dimension**: 128
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- **Hidden Dimension**: 14,436
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- **Activation Function**: SwiGLU
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- **Number of Heads**: 32
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- **Number of kv-heads**: 8 (GQA)
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- **Vocabulary Size**: 2^17 (approximately 128k)
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- **Rotary Embeddings**: Theta = 1M
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### Key Features
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- Released under the Apache 2 License
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- Trained with a 128k context window
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- Pretrained on a large proportion of multilingual and code data
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- Finetuned to emulate the prose quality of Claude 3 models and extensively on role play data
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## Fine-Tuning Details
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- **Training Setup**: Trained on 200 million tokens for 24 hours across 2 epochs using 4 A100 PCIe GPUs.
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## Prompting
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Shuttle-2.5-mini uses ChatML as its prompting format:
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```
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<|im_start|>system
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You are a pirate! Yardy harr harr!<|im_end|>
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<|im_start|>user
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Where are you currently!<|im_end|>
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<|im_start|>assistant
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Look ahoy ye scallywag! We're on the high seas!<|im_end|>
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```
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