The GGUF quantized version of Qwen2.5-Coder-1.5B, optimized for code generation tasks, offering multiple quantization options to balance performance and resource consumption.

Natural Language ProcessingGguf

Kimi-Dev-72B is a large-scale language model developed by moonshotai. It is optimized through GGUF quantization and offers multiple quantization versions to meet different hardware requirements.

Natural Language ProcessingGguf

The GGUF quantized version of CodeGemma 2B, offering multiple quantization options to optimize performance

Natural Language ProcessingGguf

This project provides the GGUF quantized file for the Echelon-AI/Med-Qwen2-7B model, supported by Featherless AI, aiming to enhance model performance and reduce operating costs.

Natural Language ProcessingGguf

DeepSeek-R1-Distill-Qwen-14B is an optimized large language model with a parameter scale of 14B, released by DeepSeek AI. It is distilled from the Qwen architecture and offers multiple GGUF quantization versions to improve performance.

Natural Language ProcessingGguf

This project provides optimized GGUF quantized files, which can significantly improve model performance. These quantized files are supported by Featherless AI. Users can run any desired model by paying a small fee.

Natural Language ProcessingGguf

Mistral-7B-v0.1 is a pre-trained generative large language model with 7 billion parameters, which outperforms the Llama 2 13B model in multiple benchmark tests. It adopts an advanced Transformer architecture design, including Grouped Query Attention and Sliding Window Attention mechanisms.

Natural Language ProcessingPytorchEnglish

Qwerky-QwQ-32B is a large language model with 32B parameters, specializing in text generation tasks.

Natural Language ProcessingGguf

This project provides the GGUF quantized files for the Vikhr-Nemo-12B-Instruct model, which is a large language model with 12 billion parameters and is specifically optimized for instruction-following tasks. By using various quantization techniques (such as IQ4_XS, Q2_K, Q3_K_M, Q4_K_M, Q5_K_M, Q6_K, Q8_0, etc.), the model size is compressed, enabling it to run efficiently on consumer-grade hardware while maintaining good performance.

Natural Language ProcessingGguf

This is a 7B parameter model based on the Mistral architecture, optimized through quantization, offering various GGUF quantization versions to meet different hardware requirements.

Natural Language ProcessingGguf

This is a GGUF quantized version based on the Meta-Llama-3-8B-Instruct model, optimized by the Featherless AI team. The model has undergone various quantization processes, significantly improving performance and reducing resource requirements, making it suitable for deployment on various hardware.

Natural Language ProcessingGguf