Hahmdong/SPUPER-qwen3.5-9b-quanquer-add-quanter1

VISIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 26, 2026Architecture:Transformer Featherless Exclusive Cold

Hahmdong/SPUPER-qwen3.5-9b-quanquer-add-quanter1 is a 9 billion parameter language model, fine-tuned by Hahmdong from the SPUPER-qwen3.5-9b-quanquer-add base model. Trained using the TRL framework, this model is designed for general text generation tasks, leveraging its 32768 token context length for comprehensive understanding. It specializes in generating coherent and contextually relevant responses based on user prompts.

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Model Overview

Hahmdong/SPUPER-qwen3.5-9b-quanquer-add-quanter1 is a 9 billion parameter language model, fine-tuned by Hahmdong. It is built upon the SPUPER-qwen3.5-9b-quanquer-add base model and was trained using the TRL (Transformer Reinforcement Learning) framework, specifically employing a Supervised Fine-Tuning (SFT) procedure.

Key Capabilities

  • General Text Generation: Capable of generating diverse and contextually appropriate text based on given prompts.
  • Fine-tuned Performance: Benefits from SFT training, which enhances its ability to follow instructions and produce relevant outputs.
  • Extended Context: Features a 32768 token context length, allowing it to process and generate longer, more complex sequences while maintaining coherence.

Good For

  • Conversational AI: Generating responses in dialogue systems or chatbots.
  • Content Creation: Assisting with writing tasks, such as drafting articles, summaries, or creative content.
  • Question Answering: Providing detailed answers to a wide range of queries by leveraging its extensive context window.

This model is a direct fine-tune, indicating an optimization for specific performance characteristics derived from its base model and training methodology.

Finetunes
2 models