3d2da94ce2
- Complete transformer implementation from scratch - Training pipeline with gradient accumulation and mixed precision - Optimized inference with KV caching - Multi-format data processing (PDFs, images, code, text) - Comprehensive documentation - Apache 2.0 license - Example training plots included in docs/images/
36 lines
786 B
Python
36 lines
786 B
Python
"""
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SheepOp LLM - A modern language model implementation
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Optimized for production RAG systems
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"""
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from .transformer import TransformerModel
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from .attention import MultiHeadAttention, PositionalEncoding
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from .blocks import TransformerBlock, FeedForward
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from .optimized_attention import (
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OptimizedMultiHeadAttention,
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RetrievalCache,
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OptimizedInference,
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KVCache,
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)
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from .prefetching import (
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PrefetchDataLoader,
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LookaheadRetriever,
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BatchPrefetcher,
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)
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__all__ = [
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'TransformerModel',
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'MultiHeadAttention',
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'PositionalEncoding',
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'TransformerBlock',
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'FeedForward',
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'OptimizedMultiHeadAttention',
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'RetrievalCache',
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'OptimizedInference',
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'KVCache',
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'PrefetchDataLoader',
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'LookaheadRetriever',
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'BatchPrefetcher',
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]
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