SCL2025/KG-R1-CWQ-no-retrieval-reward
TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kPublished:Apr 26, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The SCL2025/KG-R1-CWQ-no-retrieval-reward is a 3.1 billion parameter language model developed by SCL2025. This model is designed for general language understanding and generation tasks, featuring a substantial 32768-token context length. It is suitable for applications requiring extensive contextual awareness and efficient processing of long inputs.
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Model Overview
The SCL2025/KG-R1-CWQ-no-retrieval-reward is a 3.1 billion parameter language model developed by SCL2025. It is characterized by its significant 32768-token context window, enabling it to process and generate responses based on very long input sequences. This model is released under the Apache-2.0 license, promoting broad usability and integration into various projects.
Key Capabilities
- Extended Context Handling: Processes inputs up to 32768 tokens, making it suitable for tasks requiring deep contextual understanding over lengthy documents or conversations.
- General Purpose Language Model: Designed to handle a wide array of natural language understanding and generation tasks.
Good For
- Applications requiring analysis or summarization of long texts.
- Conversational AI systems that need to maintain context over extended dialogues.
- Tasks where the ability to process and generate based on large amounts of information is crucial.