# Large Parameter Model

Seed-Coder-8B-Reasoning is a large language model with 8B parameters developed by ByteDance-Seed, focusing on code generation and reasoning tasks.

This model is a Japanese automatic speech recognition (ASR) model based on the FastConformer architecture, developed by NVIDIA and converted to MLX format.

Gemma 3 27B is a large-scale pre-trained language model developed by Google, with 27 billion parameters, suitable for various natural language processing tasks.

IndicConformer is a Conformer-based automatic speech recognition model with a hybrid CTC-RNNT architecture, specifically designed for Urdu speech transcription.

Code Llama is a series of pre-trained generative text models released by Meta, specifically designed for code generation and understanding tasks. This model is a 34-billion-parameter Python-specific version.

This is a large Transformer model with 780 million parameters, specifically designed for music generation and transcription tasks, using anticipatory training methods.

StarChat2 is a 16-billion-parameter programming assistant model fine-tuned based on StarCoder2, excelling in conversation and code generation tasks

AutoDev Coder is a large language model fine-tuned from deepseek-coder-6.7b-instruct, specializing in code generation and programming assistance tasks.

CodeLlama-13b-Instruct is a 13-billion-parameter instruction-tuned code generation model released by Meta, specifically designed for safe instruction following and code assistant applications

Code Llama is a series of large models for code generation and understanding developed by Meta. This version is a 13B-parameter variant specialized for Python.

Code Llama 13B is a 13-billion-parameter generative code model designed for general-purpose code synthesis and understanding

Code Llama is a 7B-parameter code generation model developed by Meta, supporting general code synthesis and comprehension

InstructCodeT5+ 16B is an open-source large language model for code, featuring an encoder-decoder architecture that supports multiple modes and is suitable for a wide range of code understanding and generation tasks.

This is a large-scale Conformer-CTC model for German automatic speech recognition, trained and optimized by NVIDIA on thousands of hours of German speech data.

A speech recognition model fine-tuned on the Common Voice dataset based on facebook/wav2vec2-xls-r-1b

Hindi speech recognition model trained on the common_voice dataset

Pre-trained model based on the t5-large architecture, specializing in Python code summarization tasks

A pre-trained model based on the T5-large architecture, specializing in source code summarization tasks for the C# programming language