reader-lm-1.5b
| Property | Value |
|---|---|
| Parameter Count | 1.54B parameters |
| Model Type | Text Generation (Transformer) |
| Context Length | 256K tokens |
| License | CC-BY-NC-4.0 |
| Tensor Type | BF16 |
What is reader-lm-1.5b?
reader-lm-1.5b is a specialized language model developed by Jina AI that excels in converting HTML content to Markdown format. As part of the Reader-LM series, this 1.54B parameter model represents a powerful solution for content transformation tasks, featuring an impressive 256K token context length and multilingual support.
Implementation Details
The model is built on transformer architecture and optimized for HTML-to-Markdown conversion tasks. It can be easily implemented using the Transformers library and supports both CPU and GPU deployment. The model uses BF16 tensor type for efficient computation and memory usage.
- Simple integration with transformers library (version ≤4.43.4)
- Supports both local deployment and cloud platforms (AWS Sagemaker & Azure)
- No prefix instructions required for input processing
- Efficient processing with temperature and repetition penalty controls
Core Capabilities
- Direct HTML-to-Markdown conversion without additional prompting
- Multilingual content support
- Long context handling (256K tokens)
- Optimized for both accuracy and efficiency
- Cloud-platform compatibility
Frequently Asked Questions
Q: What makes this model unique?
The model's specialized focus on HTML-to-Markdown conversion, combined with its large context window and multilingual capabilities, makes it particularly effective for content transformation tasks. Its ability to process raw HTML without requiring specific prompting instructions simplifies implementation.
Q: What are the recommended use cases?
The model is ideal for content management systems, web scrapers, documentation tools, and any application requiring automated conversion of HTML content to Markdown format. It's particularly useful for batch processing of web content and creating clean, readable documentation from HTML sources.
