koutch/paper_llama_llama3.1-8b_train_sft_train_no_think
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Jan 16, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The koutch/paper_llama_llama3.1-8b_train_sft_train_no_think is an 8 billion parameter Llama 3.1 instruction-tuned model, fine-tuned by koutch. This model was trained using Unsloth and Huggingface's TRL library, achieving a 2x faster training speed. It is designed for general instruction-following tasks, leveraging the Llama 3.1 architecture for efficient performance.
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Model Overview
The koutch/paper_llama_llama3.1-8b_train_sft_train_no_think is an 8 billion parameter instruction-tuned language model developed by koutch. It is fine-tuned from the unsloth/meta-llama-3.1-8b-instruct-bnb-4bit base model, leveraging the Llama 3.1 architecture.
Key Characteristics
- Architecture: Based on the Llama 3.1 model family.
- Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Efficiency: This model was fine-tuned with Unsloth and Huggingface's TRL library, resulting in a 2x faster training process compared to standard methods.
- Context Length: Supports a context length of 32768 tokens.
Good For
- Instruction Following: Optimized for general instruction-following tasks due to its instruction-tuned nature.
- Efficient Deployment: The 8B parameter size makes it suitable for applications requiring a capable model that can be deployed efficiently.
- Research and Development: Provides a base for further experimentation and fine-tuning, particularly for those interested in Unsloth's training optimizations.