smshahbaj/RIFA-FLASH-1.7B

TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Aug 27, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

RIFA-FLASH is a 1.7 billion parameter fine-tuned model developed and maintained by SM Shahbaj, part of the RIFA model family. This model is presented as a higher-capacity variant within its family. It is available in various GGUF quantization formats, including Q5_K_M, for flexible deployment. The model's primary utility is for general text generation tasks, leveraging its fine-tuned nature for improved performance.

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RIFA-FLASH Model Overview

RIFA-FLASH is a 1.7 billion parameter language model developed and maintained by SM Shahbaj. It is positioned as a higher-capacity, fine-tuned model within the broader RIFA model family. This model is designed for general text generation and understanding tasks, building upon its fine-tuned architecture.

Key Characteristics

  • Model Family: Part of the RIFA series by SM Shahbaj.
  • Parameter Count: Features 1.7 billion parameters, offering a balance between performance and computational efficiency.
  • Creator: Developed and maintained by SM Shahbaj.
  • Availability: Provided in multiple GGUF quantization formats, including Q3_K_M, Q4_K_M, Q5_K_M, Q6_K, and Q8_0, alongside standard Safetensors. The Q5_K_M quantization is recommended for general use.

Intended Use Cases

RIFA-FLASH is suitable for developers looking for a compact yet capable language model for various applications. Its availability in different GGUF formats makes it adaptable for deployment on diverse hardware configurations, from local machines to more robust inference setups. The model can be integrated using standard Hugging Face transformers library for quick prototyping and deployment.

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