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Gpt J Fourchannel 4bit
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Gpt J Fourchannel 4bit
Developed by autobots
This model has been converted to GPTQ-v2 and GGML formats, supports CPU execution, and is suitable for quantized inference tasks.
Downloads 39
Release Time : 4/15/2023
Model Overview
The model has undergone quantization processing, offering multiple configuration options (such as group size and activation order optimization), making it ideal for efficient inference in resource-constrained environments.
Model Features
Multi-Format Support
Provides both GPTQ-v2 and GGML quantization formats to meet diverse deployment needs.
CPU Compatibility
The GGML format is optimized for CPU, enabling execution without GPU.
Quantization Configuration Options
Supports various quantization parameter combinations, such as 128 group size and activation order optimization.
Model Capabilities
Quantized Inference
Low-Resource Deployment
English Text Generation
Use Cases
Edge Computing
Embedded Device Deployment
Run text generation models on resource-constrained devices
Reduced memory footprint achieved through quantization
Development Testing
Quantization Technique Validation
Compare performance differences across quantization configurations
Obtain the optimal quantization solution
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