DevopsEmbrace/qwen3_32B_embrace_cpt_e1_lm_head_base_tokenizer_merged_16bit
TEXT GENERATIONPricing:Input $0.408 / Cached $0.0816 / Output $1.972Concurrent Unit Cost:2Model Size:32BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Nov 21, 2025License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
DevopsEmbrace/qwen3_32B_embrace_cpt_e1_lm_head_base_tokenizer_merged_16bit is a 32 billion parameter Qwen3 model developed by DevopsEmbrace. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its large parameter count and 32768 token context length for robust performance.
Loading preview...
Model Overview
This is a 32 billion parameter Qwen3 model, developed by DevopsEmbrace, which has been fine-tuned for enhanced performance. It leverages the Qwen3 architecture and boasts a substantial context length of 32768 tokens, making it suitable for processing extensive inputs and generating comprehensive outputs.
Key Capabilities
- Efficient Fine-tuning: The model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x speed improvement during the training process compared to standard methods.
- Large Scale: With 32 billion parameters, it is capable of handling complex language understanding and generation tasks.
- Extended Context: A 32768 token context window allows for deep contextual understanding and long-form content generation.
Good For
- Applications requiring a powerful, large-scale language model.
- Tasks benefiting from efficient fine-tuning methodologies.
- Scenarios where a broad context window is crucial for performance.