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Index-1.9B-32K is a language model with only 1.9 billion parameters, yet it supports a context length of 32K (meaning this extremely small model can read documents of over 35,000 words in one go). The model has undergone Continue Pre-Training and Supervised Fine-Tuning (SFT) specifically for texts longer than 32K tokens, based on carefully curated long-text training data and self-built long-text instruction sets. The model is now open-source on both Hugging Face and ModelScope. Index-1.9B-32K is a language model with only 1.9 billion parameters, yet it supports a context length of 32K (meaning this extremely small model can read documents of over 35,000 words in one go). The model has undergone Continue Pre-Training and Supervised Fine-Tuning (SFT) specifically for texts longer than 32K tokens, based on carefully curated long-text training data and self-built long-text instruction sets. The model is now open-source on both Hugging Face and ModelScope.
**Despite its small size (about 2% of models like GPT-4), Index-1.9B-32K demonstrates excellent long-text processing capabilities**. Below are comparison results with GPT-4 and GPT-3.5-turbo-16k: **Despite its small size (about 2% of models like GPT-4), Index-1.9B-32K demonstrates excellent long-text processing capabilities**. Below are comparison results with GPT-4 and GPT-3.5-turbo-16k:
<div style="text-align: center;">
<img src="media/pk-all.png" alt="" width="800">
<p><strong>Comparison of Index-1.9B-32K with GPT-4 and other models in long-text capability</strong></p>
</div>
In a 32K-length needle-in-a-haystack test, Index-1.9B-32K achieved excellent results, as shown in the figure below. The only exception was a small yellow spot (91.08 points) in the region of (32K length, 10% depth), with all other areas performing excellently in mostly green zones.
<div style="text-align: center;">
<img src="media/needle-bench-en.png" alt="" width="900">
<p><strong>NeedleBench Evaluation</strong></p>
</div>
## Index-1.9B-32K Model Download, Usage, and Technical Report: ## Index-1.9B-32K Model Download, Usage, and Technical Report:
For details on downloading, usage, and the technical report for Index-1.9B-32K, see: For details on downloading, usage, and the technical report for Index-1.9B-32K, see:
[**Index-1.9B-32K Long Context Technical Report.md**](https://github.com/bilibili/Index-1.9B/blob/main/Index-1.9B-32K_Long_Context_Technical_Report.md) [**Index-1.9B-32K Long Context Technical Report.md**](https://github.com/bilibili/Index-1.9B/blob/main/Index-1.9B-32K_Long_Context_Technical_Report.md)
---
---
---
## Usage：Long Text Translation and Summary（Index-1.9B-32K）
- Clone the code repository for model execution and evaluation:
```shell
git clone https://github.com/bilibili/Index-1.9B
cd Index-1.9B
```
- Download the model files to your local machine.
- Use pip to install the required environment:
```shell
pip install -r requirements.txt
```
- Run the interactive tool for long text: demo/cli_long_text_demo.py
- The model will, by default, read this file: data/user_long_text.txt and summarize the text in Chinese.
- You can open a new window and modify the file content in real-time, and the model will read the updated file and summarize it.
```shell
cd demo/
CUDA_VISIBLE_DEVICES=0 python cli_long_text_demo.py --model_path '/path/to/model/' --input_file_path data/user_long_text.txt
```
- Run & Interaction Example (Translation and summarization of the Bilibili financial report released on 2024.8.22 in English --- [Original English report here](https://github.com/bilibili/Index-1.9B/tree/main/demo/data/user_long_text.txt))：
<div style="text-align: center;">
<img src="media/qa-mark.png" alt="" width="1000">
<p><strong>Translation and Summary (Bilibili financial report released on 2024.8.22)</strong></p>
</div>
## Limitations and Disclaimer ## Limitations and Disclaimer