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RAG Models - MXL Quantized & FP16 Distilled
Models Included:
MXL Quantized Models (Apple Silicon Optimized):
- e5_distilled_fp16_rag_clean - Text embeddings (224MB)
- pleias_distilled_fp16_rag_clean - Text generation (190MB)
- osmosis_distilled_fp16_clean - Advanced reasoning (2.2GB)
Original FP16 Distilled Models:
- e5_distilled_fp16_rag - Original FP16 version
- pleias_distilled_fp16_rag - Original FP16 version
- osmosis_distilled_fp16 - Original FP16 version
Usage:
from mlx_lm import load
model, tokenizer = load('LightSpeedtoOblivion/rag-models-mxl/e5_distilled_fp16_rag_clean')
Architecture:
- E5: Sentence transformer for embeddings
- PLEIAS: LlamaForCausalLM for text generation
- OSMOSIS: Qwen3ForCausalLM for reasoning
S-DNS Naming:
- lse.colony.DoX.models.e5.mxl
- lse.colony.DoX.models.pleias.mxl
- lse.colony.DoX.models.osmosis.mxl
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