SichangHe/falcon-7b-FP8-Dynamic

TEXT GENERATIONPricing:Input $0.4 / Cached $0.02 / Output $0.8Concurrent Unit Cost:1Model Size:7BQuant:FP8Context Size:32kPublished:Jun 26, 2025License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

SichangHe/falcon-7b-FP8-Dynamic is a 7 billion parameter Falcon language model, developed by SichangHe, that has been quantized to FP8 Dynamic. This model leverages FP8 Dynamic quantization for efficient inference while maintaining performance. It is designed for applications requiring a balance of computational efficiency and language understanding capabilities.

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Overview

SichangHe/falcon-7b-FP8-Dynamic is a 7 billion parameter language model based on the Falcon architecture. This model has undergone post-training quantization (PTQ) using the FP8 Dynamic scheme, specifically targeting Linear layers while ignoring the lm_head.

Key Characteristics

  • Base Model: tiiuae/falcon-7b
  • Parameter Count: 7 billion parameters
  • Quantization Scheme: FP8 Dynamic, applied to Linear layers for optimized inference.
  • Framework: Utilizes llmcompressor for the quantization process, demonstrating a practical application of efficient model deployment.

Use Cases

This model is suitable for scenarios where reduced memory footprint and faster inference speeds are critical, such as:

  • Deployment on edge devices or environments with limited computational resources.
  • Applications requiring high-throughput text generation or understanding.
  • Research into the performance and efficiency trade-offs of FP8 quantization for large language models.