lince-zero-GPTQ
| Property | Value |
|---|---|
| Parameter Count | 1.18B |
| Model Type | Text Generation / Instruction |
| License | Apache 2.0 |
| Base Model | Falcon-7B |
| Training Datasets | Alpaca & Dolly (Spanish) |
What is lince-zero-GPTQ?
Lince-zero-GPTQ is a quantized version of the Spanish instruction-tuned language model developed by CliBrAIn. It's specifically optimized for efficient deployment while maintaining performance through GPTQ quantization, offering multiple compression options including 4-bit and 8-bit variants. The model is built on Falcon-7B architecture and fine-tuned using Spanish translations of Alpaca and Dolly datasets.
Implementation Details
The model implements advanced quantization techniques with multiple options for different use cases:
- 4-bit quantization with various group sizes (32g, 128g) for optimal memory efficiency
- 8-bit quantization options for higher precision requirements
- Support for Act Order and different group sizes for balancing performance and resource usage
- Optimized for text-generation-inference and transformers library integration
Core Capabilities
- Spanish language instruction following and generation
- Multiple compression options for different hardware configurations
- Integration with popular frameworks like transformers and text-generation-webui
- Support for both CPU and GPU inference
- Optimized for production deployment with various quantization options
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized optimization for Spanish language tasks while providing multiple quantization options for efficient deployment. It's one of the few models specifically designed for Spanish instruction-following with various compression options for different hardware configurations.
Q: What are the recommended use cases?
The model is ideal for Spanish language applications requiring instruction following and text generation, particularly in resource-constrained environments. It's suitable for virtual assistants, content generation, and other Spanish language processing tasks where efficient deployment is crucial.
