RJTPP/scot0500s-deepseek-llama-8b-full
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Apr 21, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
RJTPP/scot0500s-deepseek-llama-8b-full is an 8 billion parameter Llama-based model developed by RJTPP, finetuned from unsloth/DeepSeek-R1-Distill-Llama-8B-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster finetuning. With a 32768 token context length, it is optimized for efficient deployment and performance in applications requiring a capable yet resource-conscious language model.
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Overview
RJTPP/scot0500s-deepseek-llama-8b-full is an 8 billion parameter Llama-based language model, developed by RJTPP. It is a finetuned version of the unsloth/DeepSeek-R1-Distill-Llama-8B-unsloth-bnb-4bit model, leveraging the Unsloth library for accelerated training.
Key Capabilities
- Efficient Finetuning: This model was trained 2x faster using the Unsloth library in conjunction with Huggingface's TRL library, making it a strong candidate for rapid iteration and deployment.
- Llama Architecture: Built upon the Llama architecture, it inherits robust language understanding and generation capabilities.
- Extended Context: Features a substantial context length of 32768 tokens, suitable for processing longer inputs and maintaining conversational coherence over extended interactions.
Good For
- Resource-Constrained Environments: Its efficient training and 8B parameter size make it suitable for applications where computational resources are a consideration.
- Rapid Prototyping: Ideal for developers looking to quickly finetune and deploy Llama-based models due to its optimized training methodology.
- General Language Tasks: Capable of handling a wide range of natural language processing tasks, including text generation, summarization, and question answering, within its context window.