tog/TinyLlama-1.1B-alpaca-chat-v1.0
TEXT GENERATIONConcurrency Cost:1Model Size:1.1BQuant:BF16Ctx Length:2kLicense:apache-2.0Architecture:Transformer0.0K Open Weights Warm
tog/TinyLlama-1.1B-alpaca-chat-v1.0 is a 1.1 billion parameter chat model, fine-tuned by tog on the PY007/TinyLlama-1.1B-intermediate-step-480k-1T base model. It utilizes the tatsu-lab/stanford_alpaca dataset for instruction-following capabilities, making it suitable for conversational AI applications. With a 2048-token context length, this model is designed for efficient, small-scale chat interactions.
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Model Overview
tog/TinyLlama-1.1B-alpaca-chat-v1.0 is a compact, instruction-tuned language model with 1.1 billion parameters. It is built upon the PY007/TinyLlama-1.1B-intermediate-step-480k-1T base model, indicating its lineage from the TinyLlama project focused on creating efficient, small-scale LLMs.
Key Capabilities
- Instruction Following: Fine-tuned using the tatsu-lab/stanford_alpaca dataset, this model is designed to understand and respond to user instructions effectively.
- Chat-Oriented: Optimized specifically for conversational AI tasks, making it suitable for dialogue generation and interactive applications.
- Efficient Size: With 1.1 billion parameters, it offers a balance between performance and computational efficiency, ideal for environments with limited resources.
Good For
- Lightweight Chatbots: Developing chatbots or conversational agents where resource consumption is a primary concern.
- Instruction-Based Interactions: Applications requiring the model to follow specific instructions and generate appropriate responses.
- Educational or Research Projects: Exploring the capabilities of smaller, fine-tuned language models for specific tasks.