Instructions to use procedure2012/Nimbus-Chat-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use procedure2012/Nimbus-Chat-Mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="procedure2012/Nimbus-Chat-Mini")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("procedure2012/Nimbus-Chat-Mini") model = AutoModel.from_pretrained("procedure2012/Nimbus-Chat-Mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 2,361 Bytes
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license: apache-2.0
library_name: transformers
---
# Nimbus-Chat-Mini
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<img src="figures/fig1.png" width="60%" alt="Nimbus-Chat-Mini" />
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## 1. Introduction
Nimbus-Chat-Mini is a compact assistant for on-device dialogue. Despite its size it shows strong instruction following after our distillation pipeline.
## 2. Evaluation Results
### Comprehensive Benchmark Results
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| | Benchmark | TinyTalk | Nimbus-0.5 | Breeze | Nimbus-Chat-Mini |
|---|---|---|---|---|---|
| **Core Reasoning Tasks** | Math Reasoning | 0.603 | 0.621 | 0.590 | 0.633 |
| | Logical Reasoning | 0.798 | 0.835 | 0.794 | 0.850 |
| | Common Sense | 0.774 | 0.774 | 0.766 | 0.783 |
| **Language Understanding** | Reading Comprehension | 0.714 | 0.719 | 0.735 | 0.760 |
| | Question Answering | 0.593 | 0.640 | 0.607 | 0.649 |
| | Text Classification | 0.807 | 0.822 | 0.830 | 0.849 |
| | Sentiment Analysis | 0.806 | 0.762 | 0.772 | 0.818 |
| **Generation Tasks** | Code Generation | 0.684 | 0.713 | 0.688 | 0.730 |
| | Creative Writing | 0.653 | 0.655 | 0.689 | 0.700 |
| | Dialogue Generation | 0.681 | 0.647 | 0.664 | 0.702 |
| | Summarization | 0.763 | 0.790 | 0.780 | 0.805 |
| **Specialized Capabilities** | Translation | 0.788 | 0.768 | 0.803 | 0.826 |
| | Knowledge Retrieval | 0.685 | 0.679 | 0.684 | 0.718 |
| | Instruction Following | 0.771 | 0.740 | 0.776 | 0.798 |
| | Safety Evaluation | 0.728 | 0.767 | 0.729 | 0.779 |
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### Overall Performance Summary
The Nimbus-Chat-Mini demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks.
## 3. Chat Website & API Platform
We offer a chat interface and API for you to interact with Nimbus-Chat-Mini. Please check our official website for more details.
## 4. How to Run Locally
Please refer to our code repository for more information about running Nimbus-Chat-Mini locally.
### Temperature
We recommend setting the temperature parameter to 0.6.
## 5. License
This repository is released under the apache-2.0 license. The model supports commercial use.
## 6. Contact
If you have any questions, please contact us at team@nimbus.chat.
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