Haary/TinyLlama-1.1B-indo-v1
Haary/TinyLlama-1.1B-indo-v1 is a 1.1 billion parameter causal language model based on the TinyLlama architecture, fine-tuned from TinyLlama/TinyLlama-1.1B-Chat-v1.0. This model is designed for general text generation tasks, leveraging its compact size for efficient deployment. It provides a foundation for applications requiring a small, yet capable, language model.
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Model Overview
Haary/TinyLlama-1.1B-indo-v1 is a 1.1 billion parameter language model built upon the TinyLlama architecture. It is a fine-tuned version of the TinyLlama/TinyLlama-1.1B-Chat-v1.0 base model, indicating an adaptation for specific use cases or improved performance in certain domains.
Key Characteristics
- Base Model: Derived from TinyLlama/TinyLlama-1.1B-Chat-v1.0, suggesting a foundation in chat-oriented language understanding and generation.
- Parameter Count: At 1.1 billion parameters, it falls into the category of smaller, more efficient language models, suitable for environments with limited computational resources.
Usage and Deployment
This model is provided with a Python code example demonstrating inference using the transformers library, compatible with GPTQ quantization. It requires specific versions of transformers, optimum, and AutoGPTQ for optimal performance, with instructions for both pre-built wheels and source installation. The example showcases both direct model generation and pipeline-based inference.
Good For
- Applications requiring a compact and efficient language model.
- General text generation and conversational AI tasks, given its chat-model lineage.
- Experimentation and development on resource-constrained hardware due to its smaller size.