Tesslate/Tessa-T1-32B

TEXT GENERATIONConcurrency Cost:2Model Size:32.8BQuant:FP8Ctx Length:32kPublished:Mar 24, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Cold

Tessa-T1-32B is a transformer-based React reasoning model developed by Tesslate, fine-tuned from Qwen2.5-Coder-32B-Instruct. This 32 billion parameter model is specifically designed to autonomously generate well-structured, semantic React components. It excels at integrating into agent systems for automating web interface development and frontend code intelligence, providing context-aware code solutions.

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Model Overview

Tessa-T1-32B, developed by Tesslate, is a specialized transformer-based React reasoning model. It is fine-tuned from the Qwen2.5-Coder-32B-Instruct base model, focusing on generating functional and semantic React components. This model is particularly suited for integration into agent systems, enhancing autonomous frontend development and code intelligence.

Key Capabilities

  • React-specific Reasoning: Generates accurate and semantic React components.
  • Agent Integration: Designed for seamless integration into AI-driven coding agents and autonomous frontend systems.
  • Context-Aware Generation: Understands and utilizes UI context to provide relevant code solutions.
  • Automatic Component Generation: Quickly produces React components from textual prompts.

Use Cases

  • Automated Web Development: Ideal for automating the creation of React components and integrating into larger coding systems.
  • Frontend Refactoring: Can be used to automate the optimization and semantic enhancement of existing React code.

Limitations

  • React-Focused: Its utility is primarily within React.js frameworks.
  • Complex State Management: May require manual adjustments for highly dynamic state management scenarios.
  • Complex JavaScript Logic: Some intricate JavaScript logic might necessitate post-processing.

Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

temperature
top_p
top_k
frequency_penalty
presence_penalty
repetition_penalty
min_p