DanielClough/Candle_Mistral-7B-Instruct-v0.2
DanielClough/Candle_Mistral-7B-Instruct-v0.2 is a 7 billion parameter instruction-tuned causal language model, based on the Mistral-7B-Instruct-v0.2 architecture. This model is specifically packaged in the .gguf format for use with HuggingFace/Candle, making it suitable for efficient inference within the Candle framework. It maintains the original model's capabilities for general instruction following and text generation.
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Overview
DanielClough/Candle_Mistral-7B-Instruct-v0.2 is a specialized packaging of the Mistral-7B-Instruct-v0.2 model, designed for compatibility with the HuggingFace/Candle inference framework. This 7 billion parameter instruction-tuned model provides general language understanding and generation capabilities, inheriting the strengths of its base architecture.
Key Characteristics
- Model Architecture: Based on the Mistral-7B-Instruct-v0.2, known for its strong performance in its size class.
- Parameter Count: 7 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a context window of 4096 tokens.
- Format: Provided in the
.ggufformat, specifically built for use with HuggingFace/Candle. - Inference Framework: Optimized for deployment and inference using the Candle library, which is a Rust-based deep learning framework.
Important Note
- These
.gguffiles are not compatible withllama.cppand are exclusively for use with HuggingFace/Candle. Users should refer to the original Mistral-7B-Instruct-v0.2 repository for comprehensive details regarding the model's training, capabilities, and ethical considerations.