Navyaforaa/LitGram-1.5B
TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:1.5BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 19, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
Navyaforaa/LitGram-1.5B is a 1.5 billion parameter Qwen2 model developed by Navyaforaa, fine-tuned for enhanced performance. It was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model offers a 32768 token context length, making it suitable for applications requiring efficient processing of long sequences.
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Navyaforaa/LitGram-1.5B Overview
Navyaforaa/LitGram-1.5B is a 1.5 billion parameter language model developed by Navyaforaa. This model is a fine-tuned variant of the Qwen2 architecture, designed for improved efficiency and performance.
Key Characteristics
- Architecture: Based on the Qwen2 model family.
- Parameter Count: Features 1.5 billion parameters, offering a balance between performance and computational requirements.
- Context Length: Supports a substantial context window of 32768 tokens, beneficial for tasks involving longer texts.
- Training Efficiency: The model was trained with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
Potential Use Cases
- Applications requiring efficient language processing with a moderate parameter count.
- Tasks benefiting from a large context window, such as summarization of long documents or extended conversational AI.
- Environments where faster training and deployment are critical.