laion/nemotron-terminal-corpus-unified-3160__Qwen3-8B
The laion/nemotron-terminal-corpus-unified-3160__Qwen3-8B model is a fine-tuned 8 billion parameter Qwen3-8B language model, developed by laion, with a 32K context length. It has been specifically adapted using the nemotron-terminal-corpus-unified-3160 dataset. This model is intended for tasks related to its specialized fine-tuning, though specific capabilities require further documentation.
Loading preview...
Overview
This model, laion/nemotron-terminal-corpus-unified-3160__Qwen3-8B, is an 8 billion parameter language model based on the Qwen3-8B architecture. It has been fine-tuned by laion using the nemotron-terminal-corpus-unified-3160 dataset, suggesting a specialization in areas related to terminal interactions or corpus analysis. The model was trained with a learning rate of 4e-05 over 7 epochs, utilizing a multi-GPU setup with 32 devices and a total batch size of 96.
Key Training Details
- Base Model: Qwen/Qwen3-8B
- Fine-tuning Dataset:
/e/data1/datasets/playground/ot/hf_hub/datasets--laion--nemotron-terminal-corpus-unified-3160/snapshots/d08dfc1e937a7c0f59045e75bbf6404fa7957bc6_thinking_preprocessed - Parameters: 8 billion
- Context Length: 32768 tokens
- Optimizer: AdamW (betas=(0.9, 0.98), epsilon=1e-08)
- Scheduler: Cosine with 0.1 warmup ratio
- Epochs: 7.0
Intended Uses & Limitations
Specific intended uses and limitations are not detailed in the provided model card, indicating that further information is needed to fully understand its optimal applications and potential constraints. Developers should consider the fine-tuning dataset's nature when evaluating its suitability for specific tasks.