davzoku/cria-llama2-7b-v1.3
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Aug 14, 2023License:llama2Architecture:Transformer0.0K Open Weights Cold
The davzoku/cria-llama2-7b-v1.3 model is a 7 billion parameter Llama 2-based language model fine-tuned by davzoku using QLoRA (4-bit precision) on the mlabonne/CodeLlama-2-20k dataset. This model is designed as the backbone for an end-to-end chatbot system, focusing on instruction-tuning for conversational AI applications. It leverages a 4096-token context length and is optimized for deployment in web frameworks like Next.js.
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CRIA v1.3: A Fine-Tuned Llama 2 Model for Chatbot Development
CRIA v1.3 is a 7 billion parameter language model developed by davzoku, built upon the llama-2-7b-chat-hf architecture. The project's core objective is to provide a comprehensive, end-to-end chatbot system, from model instruction-tuning to web deployment.
Key Capabilities & Training Details
- Instruction-Tuned: Fine-tuned using QLoRA (4-bit precision) to enhance conversational abilities.
- Dataset: Training was conducted on the mlabonne/CodeLlama-2-20k dataset, suggesting a potential emphasis on code-related or technical dialogue.
- Quantization: Utilizes
bitsandbytesfor 4-bit quantization (nf4type) during training, enabling efficient resource usage. - Deployment Focus: Designed to serve as the foundational model for the CRIA chat platform and integrate with web frameworks like Next.js.
Good For
- Developers building custom chatbot applications requiring a fine-tuned Llama 2 base.
- Projects focused on instruction-following and conversational AI, particularly those benefiting from a code-centric training dataset.
- Experimentation with QLoRA fine-tuning and efficient model deployment.