Instructions to use SOTAagi2030/AssistantModel-Best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SOTAagi2030/AssistantModel-Best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SOTAagi2030/AssistantModel-Best")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SOTAagi2030/AssistantModel-Best") model = AutoModel.from_pretrained("SOTAagi2030/AssistantModel-Best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,911 Bytes
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license: apache-2.0
library_name: transformers
---
# AssistantModel
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<div align="center">
<img src="figures/fig1.png" width="60%" alt="AssistantModel" />
</div>
<hr>
<div align="center" style="line-height: 1;">
<a href="LICENSE" style="margin: 2px;">
<img alt="License" src="figures/fig2.png" style="display: inline-block; vertical-align: middle;"/>
</a>
</div>
## 1. Introduction
AssistantModel is designed for interactive assistant applications. This checkpoint is selected based on the combined performance of knowledge retrieval and instruction following benchmarks, making it ideal for AI assistant deployment.
<p align="center">
<img width="80%" src="figures/fig3.png">
</p>
## 2. Evaluation Results
### Comprehensive Benchmark Results
<div align="center">
| | Benchmark | Assistant-v1 | Assistant-v2 | AssistantModel |
|---|---|---|---|---|
| **Core Reasoning Tasks** | Math Reasoning | 0.510 | 0.535 | 0.550 |
| | Logical Reasoning | 0.789 | 0.801 | 0.819 |
| | Common Sense | 0.716 | 0.702 | 0.736 |
| **Language Understanding** | Reading Comprehension | 0.671 | 0.685 | 0.700 |
| | Question Answering | 0.582 | 0.599 | 0.607 |
| | Text Classification | 0.803 | 0.811 | 0.828 |
| | Sentiment Analysis | 0.777 | 0.781 | 0.792 |
| **Generation Tasks** | Code Generation | 0.615 | 0.631 | 0.650 |
| | Creative Writing | 0.588 | 0.579 | 0.636 |
| | Dialogue Generation | 0.621 | 0.635 | 0.644 |
| | Summarization | 0.745 | 0.755 | 0.767 |
| **Specialized Capabilities**| Translation | 0.782 | 0.799 | 0.804 |
| | Knowledge Retrieval | 0.651 | 0.668 | 0.676 |
| | Instruction Following | 0.733 | 0.749 | 0.758 |
| | Safety Evaluation | 0.718 | 0.701 | 0.803 |
</div>
## 3. License
[Apache-2.0 License](LICENSE)
## 4. Contact
Open an issue on GitHub.
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