DanielClough/Candle_MistralLite
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Dec 21, 2023License:apache-2.0Architecture:Transformer Open Weights Cold
Candle_MistralLite is a 7 billion parameter language model, based on the MistralLite architecture, specifically packaged for use with the HuggingFace/Candle framework. This model is designed for efficient inference within the Candle ecosystem, offering a 4096 token context length. It is optimized for developers utilizing Candle for their machine learning applications.
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Candle_MistralLite Overview
Candle_MistralLite is a 7 billion parameter language model derived from the MistralLite architecture, specifically prepared for the HuggingFace/Candle machine learning framework. This model is provided in the .gguf format, which is compatible with Candle but not with llama.cpp.
Key Characteristics
- Architecture: Based on the MistralLite model, known for its efficiency and performance in its size class.
- Parameter Count: Features 7 billion parameters, balancing capability with computational requirements.
- Context Length: Supports a context window of 4096 tokens, suitable for a range of conversational and text generation tasks.
- Framework Specific: Exclusively built and optimized for use with the HuggingFace/Candle library, ensuring seamless integration and performance within that ecosystem.
- Configuration: Requires the
config_chat_mlconfiguration fromcandle-transformersfor proper operation.
Intended Use Cases
- Candle-based Applications: Ideal for developers building applications with the HuggingFace/Candle framework who require a capable and efficient language model.
- Efficient Inference: Suitable for scenarios where optimized inference performance within the Candle environment is a priority.
- General Text Generation: Can be applied to various tasks such as summarization, question answering, and content creation, leveraging its 7B parameters and 4K context.