FastApply-7B-v1.0
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Fastapply 7B V1.0
Overview :
FastApply-7B-v1.0 is a large language model specifically designed for code editing tasks. Built on the Qwen2.5 Coder architecture, it's fine-tuned for fast and accurate code modifications. This model rapidly generates complete file edits, supporting immediate code application tasks, making it ideal for integration into AI-powered code editors. It demonstrates high throughput and high editing accuracy in deployment, achieving speeds of approximately 150 tokens/second. Developed by Kortix and licensed under Apache-2.0, it aims to support data generation and model fine-tuning through a fast application process.
Target Users :
This product is tailored for developers and teams requiring fast and accurate code editing, particularly those utilizing AI-powered code editors. It enhances code modification efficiency, reducing manual editing time and errors.
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Use Cases
Rapidly merge code updates within an AI-powered code editor.
Provide low-cost code editing solutions for local development tools.
Achieve fast code modifications in high-throughput environments.
Features
Immediate Code Application: Quickly merge code updates, ensuring full integration of modifications.
Complete File Editing: Supports precise editing of entire code files while preserving code structure and comments.
AI Editor Integration: Seamlessly integrates with AI-powered code editors like Aider and PearAI.
Local Tool Support: Reduces the output cost of cutting-edge models, making it suitable for local development environments.
High Throughput: Achieves high throughput and editing accuracy in rapid deployment environments.
How to Use
1. Load the model and tokenizer using the Hugging Face Transformers library.
2. Prepare the input text, structuring the code and update snippets according to the specified prompt format.
3. Encode the input text for the model.
4. Invoke the model to generate a response.
5. Extract the updated code from the response, located within the `<updated-code>` tags.
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