ranjith0909/qwen3_5-9b-oppora-email-merged
VISIONConcurrent Unit Cost:1Model Size:9BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 7, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The ranjith0909/qwen3_5-9b-oppora-email-merged is a 9 billion parameter Qwen3.5-based causal language model developed by ranjith0909. This model was fine-tuned using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is designed for general language tasks, leveraging its Qwen3.5 foundation and efficient fine-tuning process.
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Model Overview
The ranjith0909/qwen3_5-9b-oppora-email-merged is a 9 billion parameter language model, fine-tuned by ranjith0909. It is based on the robust Qwen3.5 architecture, known for its strong performance across various language understanding and generation tasks.
Key Characteristics
- Base Model: Fine-tuned from
Qwen/Qwen3.5-9B. - Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
- Parameter Count: Features 9 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Potential Use Cases
This model is suitable for a variety of natural language processing applications, including:
- Text generation and completion.
- Summarization tasks.
- Question answering.
- Chatbot development.
- General-purpose language understanding.