Llama-3-Kimodo-GGML

Native GGML/GGUF text encoder used by Kimodo. This is the reusable LLM2Vec encoder only; download a matching Kimodo diffusion model separately, for example Kimodo-SMPLX-RP-v1-GGML.

From a kimodo.cpp checkout with the Hugging Face CLI installed, install both with:

scripts/download_gguf_weights.sh --output "$PWD"

The downloader installs the recommended Q8_0 variant by default. Select a different one with --text-quantization bf16|q8_0|q6_k|q5_k|q4_k|q4_k_m. Every variant is one monolithic weight GGUF and uses the same tokenizer.gguf. Kimodo reads individual tensor ranges from the monolith, so streaming one layer at a time does not require separate per-layer files.

Variant	Weight file	Size (GB)	Intended use
BF16	Llama-3-Kimodo-BF16.gguf	15.18	Reference
Q8_0	Llama-3-Kimodo-Q8_0.gguf	8.14	Recommended
Q6_K	Llama-3-Kimodo-Q6_K.gguf	6.32	Experimental
Q5_K	Llama-3-Kimodo-Q5_K.gguf	5.33	Experimental
Q4_K	Llama-3-Kimodo-Q4_K.gguf	4.39	Experimental
Q4_K_M	Llama-3-Kimodo-Q4_K_M.gguf	5.06	Preferred low-bit experiment

The published distribution contains only monolithic weight variants and one shared tokenizer. Split component files are local conversion intermediates.

Provenance and licence

The bundle is converted from Meta Llama-3-8B-Instruct and the MIT-licensed McGill LLM2Vec MNTP and supervised adapters. Built with Meta Llama 3.

LICENSE-META-LLAMA-3.txt and NOTICE accompany this distribution. Review the Meta Llama 3 Community License before use or redistribution. MANIFEST.json records the exact source commits and SHA-256 of every published artifact, plus the weight/tokenizer mapping for each quantization.